Criteria for Machinability Evaluation of Compacted Graphite Iron

Criteria for Machinability Evaluation of Compacted Graphite Iron Materials

Design and Production Planning Perspective on Cylinder Block Manufacturing

ANDERS BERGLUND

Doctoral thesis

KTH Royal Institute of Technology Department of Production Engineering

Machine and Process Technology

Stockholm, Sweden 2011

TRITA‐IIP‐2011‐10 ISSN 1650‐1888 ISBN 978‐91‐7501‐159‐2 KTH Industriell produktion Maskin och processteknologi SE‐100 44 Stockholm, Sverige Akademisk avhandling som med tillstånd av Kungliga Tekniska högskolan framlägges till offentlig granskning för avläggande av teknologie doktorsexamen i industriell produktion fredagen den 2 december 2011 kl 09:00 i sal F3, Kungliga Tekniska högskolan, Lindstedtsvägen 26, Stockholm. Copyright © Anders Berglund Tryck: Universitetsservice US‐AB

III

ABSTRACT

The Swedish truck industry is looking for new material solutions to achieve lighter engines with increased strength to meet customer demands and to fulfil the new regulations for more environmentally friendly trucks. This could be achieved by increasing the peak pressure in the cylinders. Consequently, a more efficient combustion is obtained and the exhaust lowered. This, however, exposes the engine to higher loads and material physical properties must therefore be enhanced. One material that could meet these demands is Compacted Graphite Iron (CGI). Its mechanical and physical properties make it ideal as cylinder block material, though there are drawbacks concerning its machinability as compared to other materials that are commonly used for the same purpose. Knowledge about machining of the material and its machinability is consequently inadequate.

The main goal of this thesis is to identify and investigate the effect of the major factors and their individual contributions on CGI machining process behaviour. When the relationship between the fundamental features; machinability, material microstructure, and material physical properties, are revealed, the CGI material can be optimized, both regarding the manufacturing process and design requirements. The basic understanding of this is developed mainly through experimental analysis as, e.g., machining experiments and material characterization.

The machining model presented in this thesis demonstrates the influence of material and process parameters on CGI machinability. It highlights machinability from both design and production planning perspectives. Another important objective of the thesis is an inverse thermo−mechanical FE model for intermittent machining of CGI. Here, experimental results obtained from a developed simulated milling method are used as input data, both to calibrate and validate the model. With these models, a deeper understanding is obtained regarding the way to achieve a stable process, which is the basis for future optimization procedures. The models can therefore be used as a foundation for the optimization of CGI component manufacturing.

Keywords: Metal Cutting, Compacted Graphite Iron (CGI), Machinability, Design of Experiments (DoE), Inverse Finite Element (FE) Modelling, Simulated Milling Method

V

PREFACE

This doctoral thesis is based on research work conducted at the department of Production Engineering at the Royal Institute of Technology in Stockholm, Sweden during 2006 to 2011. It has been supported by the VINNOVA MERA program and the VINNOVA FFI program.

This work would not have been possible without the support of several people. To start with, I would like to show gratitude and respect towards my supervisor, Professor Cornel Mihai Nicolescu, for sharing his deep knowledge in the field of metal cutting and teaching me scientific thinking. He has always supported me and made time for me in his otherwise so busy schedule. Secondly, a special thank to my roommates Dr Andreas Archenti and Tech Lic Mathias Werner. Thanks Andreas for your positive attitude. It has been very motivating to work with you and you have given me great ideas. However, most of all I would like to thank you for being such a good friend. Thanks Mathias, for your support, it has been a pleasure to work with you. My colleague and dear friend, Tech Lic Lorenzo Daghini is also acknowledged for always having his door open to me and helping out in all situations. You have also introduced me to the Italian culture.

All my other colleagues and friends at the department of Production Engineering are also recognized for giving me the opportunity to work in such a stimulating environment. Thanks for showing me great patience when spreading CGI graphite dust in the workshop during the years of machining thousands of kilos cast iron workpieces. A special acknowledgement goes to technician Mr Jan Stamer for his technological creativity and deep knowledge in all fields which has been very inspiring. Your help during preparation and execution of all machining experiments has been invaluable. Thank you, Dr Thomas Lundholm for initiating the “Fredagsrus” tradition and making us push ourselves to the limit in the running tracks of Lill‐Jansskogen.

I also appreciate the help from all other members in the OPTIMA CGI and OPTIMA phase two project; Scania, Volvo Powertrain, Sandvik Coromant, Sintercast, Novacast, Federal‐Mogul, Chalmers University of Technology, Jönköping University and Swerea SWECAST. A special thank to Dr Henrik Svensson at Swerea SWECAST for material characterization and to Mikael Hedlind at KTH for workpiece design contribution to the development of the simulated milling method.

Finally I would like to thank my family.

Hope you will have a good reading.

Stockholm, November 2011

VII

”Ett materials bearbetbarhet är en synnerligen sammansatt egenskap, varför det fordras en ganska omfattande utrustning för att densamma på ett rationellt sätt skall kunna bestämmas. Bortsett från att alla prov måste utföras av tränad, kunnig och erfaren personal, måste den tekniska utrustningen vara speciellt avpassad för försöksändamål. Försöken måste nämligen utföras laboratoriemässigt, men det oaktat i möjligaste mån i verkstadsmässig form, för att de erhållna resultaten skola bli så användbara som möjligt.” Professor Ragnar Woxén, 1944

IX

TABLE OF CONTENTS

PUBLICATION LIST ................................................................................................ XI

NOMENCLATURE AND ABBREVIATIONS ............................................................. XIII

1 INTRODUCTION ............................................................................................... 1

1.1 Project and research background ............................................................................... 1 1.2 Scope and aim of the thesis ........................................................................................ 2 1.3 Thesis outline and relation to the appended papers .................................................. 4

2 STATE OF THE ART, CGI MATERIAL PROCESSING ............................................... 5

2.1 Compacted Graphite Iron (CGI) ................................................................................... 5 2.2 CGI machining process behaviour ............................................................................... 8 2.3 Cutting tool temperature modelling ......................................................................... 12

3 A MACHINING MODEL FOR CGI MACHINABILITY STUDIES .............................. 13

3.1 Method to evaluate machinability ............................................................................ 15 3.2 Influence of microstructure on CGI machinability in milling ..................................... 17 3.3 Influence of carbide promoting elements on CGI machinability in milling ............... 22 3.4 Influence of cutting parameters on CGI machinability in milling .............................. 28 3.5 Machinability of CGI from a process planning perspective ....................................... 35

4 A NOVEL METHOD TO STUDY THE CHARACTERISTICS OF THE INTERMITTENT CUTTING PROCESS ......................................................................................... 45

4.1 Simulated milling in turning operation ..................................................................... 45 4.2 Experimental evaluation of the technique ................................................................ 48 4.3 Conclusions ............................................................................................................... 53

5 AN INVERSE THERMO–MECHANICAL FE MODEL FOR INTERMITTENT MACHINING OF CGI ....................................................................................... 55

5.1 Thermo−mechanical FE model for intermi ent machining of CGI ........................... 55 5.2 Conclusions ............................................................................................................... 64

6 DISCUSSION AND CONCLUSIONS ................................................................... 65

6.1 Discussion and conclusions ....................................................................................... 65 6.2 Future research ......................................................................................................... 66

REFERENCES ....................................................................................................... 69

APPENDED PAPERS ............................................................................................. 75

XI

PUBLICATION LIST

APPENDED PAPERS

The following papers constitute the basis of this thesis.

Paper A Berglund, A., Nicolescu, C.M., Richnau, K., “Effect of carbide promoting elements on CGI material processing”, Proceedings of CIRP 2nd International Conference on Process Machine Interactions, Vancouver, Canada, 2010, ISBN: 978‐0‐9866331‐0‐2

Paper B Berglund, A, Nicolescu, C.M., Svensson, H., “The Effect of Interlamellar Distance in Pearlite on CGI Machining”, ICME 2009: International Conference on Mechanical Engineering, Tokyo, Japan, 2009, ISSN: 2070‐3740

Paper C Berglund, A., Grenmyr, G., Nicolescu, C.M., Kaminski, J., “Analysis of Compacted Graphite Iron Machining by Investigation of Tool Temperature and Cutting Force”, Proceedings of 1st International Conference on Process Machine Interactions, Hannover, Germany, 2008, ISBN: 978‐3‐939026‐95‐2

Paper D Berglund, A., Nicolescu, C.M., “Investigation of the Effect of Microstructures on CGI Machining”, The Swedish Production Symposium, Gothenburg, Sweden, 2007, TRITA‐IIP‐07‐06

Paper E Grenmyr, G., Berglund, A., Kaminski, J. and Nicolescu, C.M., “Investigation of tool wear mechanisms in CGI machining”, International Journal of Mechatronics and Manufacturing Systems, Vol. 4, No. 1, pp. 3–18, 2011, ISSN: 1753‐1039

NOT APPENDED PAPERS

The following papers contribute but are not appended to this thesis.

Paper F Berglund, A., Archenti, A., Nicolescu, C.M., “Analytical modelling of CGI machining system dynamic behaviour”, The International 3rd Swedish production symposium, Gothenburg, Sweden, 2009

Paper G Grenmyr, G., Berglund, A., Kaminski, J., Nicolescu, C.M., “Analysis of Machining Compacted Graphite Iron (CGI) by Join Investigation of Tool Temperature, Cutting Force and Tool Wear”, The Swedish Production Symposium, Stockholm, Sweden, 2008, TRITA‐IIP‐08‐12

Paper H Berglund, A., Nayyar, V., Nicolescu, C.M., Kaminski, J., “Machinability of Compacted Graphite Iron in Continuous and Intermittent Machining”, in manuscript

Research work related to this thesis has also been presented in a licentiate thesis:

Berglund, A., “Characterization of factors interacting in CGI machining: machinability, material microstructure, material physical properties”, Licentiate Thesis, KTH Royal Institute of Technology, Stockholm, Sweden, 2008, ISBN 978‐91‐7415‐158‐9

XIII

NOMENCLATURE AND ABBREVIATIONS

ALE ‐ arbitrary lagrangian‐eulerian

ap ‐ depth of cut [mm]

ae ‐ width of cut [mm]

CGI ‐ compacted graphite iron

cp ‐ specific heat of the material [J/(kg∙K)]

Dc ‐ diameter of the milling cutter [mm]

DoE ‐ design of experiments

E ‐ elastic modulus [GPa]

FE ‐ finite element

fz ‐ feed, milling [mm/tooth]

K ‐ thermal conductivity [W/(m∙K)]

K0 ‐ thermal conductivity of unalloyed iron [W/(m∙K)]

LOM ‐ light‐optic microscope

LGI ‐ lamellar graphite iron

‐ volumetric energy addition [W/m3]

ρ ‐ density [kg/m3]

RCD ‐ rotating cutting force dynamometer

Rp0.2 ‐ yield strength [MPa]

SEM ‐ scanning electron microscope

SGI ‐ spheroidal graphite iron

t ‐ time [sec]

T ‐ temperature [°C]

UTS ‐ ultimate tensile strength [MPa]

vc ‐ cutting speed [m/min]

γp ‐ axial rake angle [°]

γf ‐ radial rake angle [°]

κr ‐ entering angle [°]

Z ‐ number of inserts

1

1 INTRODUCTION

This chapter describes the background of the research project, in which most of the studies presented have been conducted. The structure of the thesis and the research approach are also addressed.

1.1 Projectandresearchbackground

The automotive industry in Sweden is of great importance to the general welfare of the country. During 2010, 13% of the total industrial investment in Sweden was put in the automotive industry and in the first quarter of 2011 12% of the total Swedish export was linked to the automotive industry. Around 120 000 people were working directly in the automotive industry in Sweden in 2010. Furthermore, in the year 2009, during the global economic crisis 27% of all industrial investment in research was put in the transportation sector, where the automotive industry is the dominating area [1], [2]. This is one reason why Swedish automotive companies are so successful.

One of the research projects that have been supported by the Swedish automotive industry together with the Swedish Governmental Agency for Innovation Systems (VINNOVA) is the OPTIMA project, which started in 2006. The goal of the project was to study the interaction between the machining process, the material and the casting process of Compacted Graphite Iron (CGI) and in the end develop a machinability and casting model for CGI. The reason why the project was initiated was the Swedish automotive industry’s great interest in the material. Its mechanical and physical properties (75% higher tensile strength [3]) make it ideal as cylinder block material, though there are drawbacks concerning its machinability as compared to other materials that are commonly used as for the same purpose, e.g., gray iron. The knowledge about machining of the material and its machinability is consequently inadequate. For a successful implementation of CGI as engine material it is necessary to obtain deeper knowledge about the material and its machinability. As CGI is a material family [4] it is also critical to investigate the effect of the variation of chemical composition on machinability. This has initiate several research studies throughout the years but there is still a lack of deeper knowledge in what factors affect the machinability of CGI.

In order to successfully implement CGI as cylinder block or cylinder head material, it is first necessary to obtain a robust machining and casting process. Then it is possible to optimize the production lines to achieve the required process accuracy and high productivity. Generally, a robust machining process is not affected by the operator handling the machine, material variations or time factors. The robustness of the machining process is more specifically described with regards to a certain quantifiable response, e.g., surface roughness, tool life or machine down time. For example, a machining process is robust, considering surface roughness, if the quality of the surface stays within the tolerances, even if, e.g., a tougher material suddenly is introduced. However, in order to achieve a robust machining process it is first essential to understand which factors affect the machining process behaviour, and thereby the machinability. It is only when these factors are found, and their

2

influence on the machining process behaviour is fully understood, that optimization can be performed, both from a design perspective and a process planning perspective. This will allow for a highly productive component manufacturing with high process accuracy.

Design perspective refers to the parameters that have to be addressed in the production development process of a new engine. In addition to the usual parameters related to the product functionality, in the early stage, proper material physical properties for the engine are set. The material physical properties of the engine are obviously of greatest importance for design but not sufficient. The cast cylinder block will need to be machined in order to fulfil the engineering requirements (e.g., geometrical tolerances). It is therefore, important that also the machinability of the material is considered in this early stage. In this thesis, the major focus is on machining of cylinder blocks. No consideration is therefore taken on the design requirements, regarding material physical properties of the engine, even if these cannot by any means be neglected.

1.2 Scopeandaimofthethesis

The main goal of this thesis is to identify and investigate the effect of the major factors and their individual contributions on CGI machining process behaviour. When the relationship between the fundamental features; machinability, material microstructure, and material physical properties, are revealed, then the CGI material can be optimized, both regarding the manufacturing process and design requirements. A machinability model will be presented that demonstrates the most important features affecting intermittent machining of CGI. The model consists in two sub‐models, see Figure 1.

Figure 1: Illustration of the CGI machinability model with its two sub‐models.

The first sub‐model is a CGI machining model for milling, illustrating machinability both from a design perspective and from a process planning perspective. This model is mainly developed based on the results of three larger full factorial design of experiments (DoE) studies. Full factorial studies have advantages over “one factor at the time studies” as they not only show single factor effects but also illustrate the

CGI Machinability model

Sub‐model:

CGI Machining model

Sub‐model:

Inverse Thermo−Mechanical FE model

INTRODUCTION

3

factors´ relation to each other. The presented machining model in this thesis is based solely on full factorial DoE studies, in contrast to most other published work concerning machinability of CGI.

The other sub‐model is an inverse thermo−mechanical Finite Element (FE) model for intermittent machining of CGI. This model illustrates the thermal and mechanical load distributions on the chip and insert. These are important factors affecting tool wear. The model is required as it is difficult to investigate the cutting zone physics during chip removal, especially in milling, as sensor placement is difficult and often practically undoable due to the rotating cutting tool. Experimental results have been used as input data in the model. E.g., the used CGI material model in the FE representation is described by the material physical properties and by the response of the material to thermal and mechanical stresses as obtained from experimental investigations. Furthermore, IR camera measurements of cutting tool temperature have been performed in intermittent machining of CGI and used to both calibrate and validate the FE model.

A complete characterization of the machinability of CGI is not possible as there are many factors that affect the machining process behaviour of the material. However, by focusing on the most significant factors and keeping other factors constant, important trends can be found.

No attempt will be made to optimize the material or the machining process in this thesis. This should be done with respect to the specific design requirements and manufacturing process and system for the existent component manufacturing situation. However, the model presented in this thesis may be used as a foundation for optimization procedures concerning:

1. Optimization of the CGI chemical composition and thereby establishing decision rules for material design.

2. Process planning, as selecting proper process parameters for the specific CGI component manufacturing situation. From a process planning perspective, the model can be used not only when selecting the basic process parameters, as cutting speed and feed, but also when considering component configuration, milling cutter positioning with respect to the workpiece, milling cutter diameter and number of inserts.

The work, presented in this thesis, is related to face milling of CGI. However, the methodology used for acquiring deeper understanding of the machining process behaviour of the material is general, and could be extended to other types of materials or in other machining operations, e.g., turning and drilling. In this thesis, the same type of standard cemented carbide insert with K20W coating has been used for all machining experiments in the different DoE studies. The choice of the cutting insert was motivated by the fact that it is the most commonly used cutting insert and also the recommended insert for face milling of both gray iron machining and CGI machining, at least in rough machining of cylinder blocks, which is an important case study in this thesis. The choice of coated cemented carbides has also shown relatively high performance, in relation to gray iron. It is therefore not economically justified to go over to other more expensive tools such as CBN. As the same type, and number of inserts, has been used for all experiments, common conclusions for all DoE studies can be drawn. The same type of milling cutter has also been used for all machining experiments. Furthermore, all machining

4

experiments have been performed in the same machining centre, with the same type of clamping. However, some results have been verified in industrial environment, such as milling of real cylinder block components. Reference cutting data have been used in all DoE studies in order to validate the results from the different experiments.

1.3 Thesisoutlineandrelationtotheappendedpapers

Five appended papers constitute the basis of this thesis (four conference contributions and one journal paper). The thesis has six chapters. There is a short introduction to each chapter that address what will be discussed.

The second chapter of the thesis is a state‐of‐the art study of CGI material processing and modelling of cutting tool temperature, introducing the reader to the subject of CGI machining. The third chapter illustrates some important factors affecting CGI machinability. Here, the CGI machining model will be presented. These results come from several machining experiments. This chapter is based on Paper A, B, D and E. In Paper A, the effect of carbide promoting elements on CGI machinability is investigated. Paper B and D illustrate the effect of microstructure on CGI machinability. Paper E, contributes to the CGI machining model demonstrating the effect of microstructure on CGI tool wear behaviour.

In the fourth chapter the cutting tool temperature will be evaluated in intermittent machining of CGI. A novel method will be presented which enables a milling operation to be reproduced in turning application. This method opens new possibilities for refined studies of the intermittent machining process behaviour. This is achieved by the development of a novel method applied to a special designed workpiece.

The fifth chapter illustrates a developed inverse thermo−mechanical FE model in intermittent machining of CGI. Data is extracted from the cutting tool temperature studies, presented in Chapter 4, and used both to calibrate and validate the FE model. Furthermore, results obtained from material characterization are also used in the FE model. The FE model, presented in this chapter, is a developed version of the model presented in Paper C.

The last chapter concludes the work and addresses some opportunities for future research in the field.

5

2 STATE OF THE ART, CGI MATERIAL PROCESSING

The first section of this chapter introduces the CGI material to the reader. Then, a state‐of‐the‐art is presented, regarding CGI machining, focused on milling. Some earlier work in the field of temperature modelling is also addressed.

2.1 CompactedGraphiteIron(CGI)

Cast iron is a family of alloys divided into several classes, defined by their graphite morphology and metallic matrix structure. There are mainly three different classes of cast irons classified by their graphite morphology; lamellar graphite iron (LGI), compacted graphite iron (CGI) and spheroidal graphite iron (SGI). LGI, commonly known as gray iron or flake graphite iron has a stable eutectic with graphite shaped as lamellas or flakes, see Figure 2a. In Figure 2c, SGI is illustrated. It is also called ductile iron or nodular cast iron and has a stable eutectic with the graphite shaped as spheroids or nodules. The third class of cast iron is CGI which has a stable eutectic with a worm‐like shaped graphite, also called compacted graphite or vermicular graphite, see Figure 2b [5].

(a) (b) (c)

Figure 2: Microstructure of (a) gray iron, (b) CGI and (c) ductile iron (source Sintercast).

According to the ISO standard 16112:2006, proper CGI should contain a minimum of 80% of the graphite particles in vermicular form and no flake graphite should be present. In other words; the nodularity should not exceed 20% [6]. The nodularity value is a measure of the roundness of the graphite particles. A cast iron material with a nodularity of 100%, solely contain graphite nodules and it is therefore ductile iron.

6

In order to obtain the nodularity value, first a two‐dimensional polished surface of the material needs to be prepared. The surface will be studied with image analysis. The roundness shape factor is needed according to

4

Equation 1

where A is the area of the graphite particle, lm is the maximum axis length of the graphite particle and Am is the area of a circle with the diameter lm. Secondly, the roundness value of each graphite particle in the polished surface is used to differentiate between the three graphite forms. A graphite particle with a roundness value of 0.625‐1.000 is considered to have nodular form (ISO form VI), a roundness value of 0.525‐0.625 intermediate form (ISO form IV and V) and if it has a roundness value of less than 0.525 compacted form (ISO form III). Flake graphite and other under modified structures are not included in the analysis, as they are not permitted in the compacted graphite iron structure. Only graphite particles having lm exceeding 10 µm are taken into account in the evaluation. The percentage of nodularity can then be calculated with

%∑ 0.5∑

∑100

Equation 2

where Anodules is the area of graphite particles classified as having nodular form, Aintermediates is the area of graphite particles classified as having intermediate form and Aall particles is the total area of all graphite particles having lm exceeding 10 µm [5], [6].

In the following section, the procedure to produce CGI, its material physical properties and its characteristics as engine material, will be presented.

2.1.1 CastingofCGI

There are several commercial casting methods available on the market to produce CGI, e.g., the Sintercast method [7], Graphyte batch and the Graphyte flow process [8]. However, the basic procedure of producing CGI is to carefully monitor and control the amount Magnesium (Mg) in the melt. The amount of Mg affects the graphite form, and therefore also the material physical properties of the cast component [9]. If there is not sufficient magnesium, the graphite begins to grow with a flake morphology during solidification, which reduces the strength of the material drastically. Too high concentration of Mg, on the other hand, leads to nodular graphite which results in undesirable properties [7]. The magnesium content must be controlled simultaneously with the inoculation level in order to produce high quality CGI microstructures. Postinoculation can suppress carbide formation, practically in thin walls but it provides more sites for graphite precipitation which favours the growth of spheroidal rather than compacted graphite particles [9].

STATE OF THE ART, CGI MATERIAL PROCESSING

7

The chemical composition of the melt also affects the ferrite/pearlite ratio. This strongly affects the material physical properties and therefore also the machinability. The pearlite content is mainly controlled by the pearlite promoting elements Copper (Cu) and Tin (Sn). These act as diffusion barriers, making carbon diffusion from the austenite into the graphite harder; hence pearlite will preferably be formed at the solid state transformation [10].

Two other parameters that need to be considered during casting are the cooling and solidification rate which are affected by the section thickness. These parameters influence coarseness of the pearlite and the nodularity and thus the material physical properties [9]. Overall, process control while casting CGI is highly important.

2.1.2 MaterialphysicalpropertiesofCGI

The main factors setting the mechanical properties of CGI materials both at room temperatures and at elevated temperatures are the graphite morphology and the metallic matrix. The graphite morphology and the metallic matrix are furthermore mainly affected by the chemical composition, inoculation level and the section thickness, as mention above. However since the matrix can be controlled in a similar way for the different morphologies, the main difference in properties between the cast irons will be due to the graphite morphology.

In gray iron, the graphite flakes have sharp edges which give the material its characteristic properties. It has good damping properties and heat conductivity and also excellent machinability. On the negative side, gray iron has, in some applications, unsatisfactory strength and thus alloys have to be added, leading to difficulties in machinability. Ductile iron has spheroidal shaped graphite particles; it has excellent strength to the cost of machinability, and also presents problems in casting. CGI has vermicular graphite particles, with stubby flakes and small amounts of graphite spheroids, resulting in both material properties and foundry processing characteristics that are intermediately between those of gray and ductile iron [9], [11]. It exhibits some of the castability of gray iron, but with higher strength and ductility. Compared to ductile iron, it has better thermal conductivity, machinability and damping capacity [12]. Typical mechanical properties of gray iron, CGI and ductile iron can be seen in Table 1.

Table 1: Typical material physical properties of gray iron, CGI and ductile iron [13].

Property Gray Iron CGI Ductile Iron Tensile strength [MPa] 250 450 750 Elastic modulus [GPa] 105 145 160 Elongation [%] 0 1.5 5 Thermal conductivity [W/(m∙K)] 48 37 28 Relative damping capacity 1 0.35 0.22 Hardness [BHN 10/3000] 179‐202 217‐241 217‐255 R‐B Fatigue [MPa] 110 200 250

8

2.1.3 CGIasenginematerial

CGI is used in several applications today. Exhaust manifolds, hydraulic housings and brackets, and to large castings as ingot moulds, are some examples [9]. However, CGI has also great potential to be the engine material of tomorrow, especially regarding heavy duty diesel engines. Today, there are some truck diesel engine components produced in CGI, e.g.:

Scania V8 (16.4 L), cylinder block

Navistar (12.4 L), cylinder block

MAN (12.4 L), cylinder block

Hyundai (12.3 L) , cylinder head

Ford‐Otosan (9.0 L), cylinder block and cylinder head

DAF (12.9 L), cylinder block and cylinder head [14]

The main motives of using CGI as engine material are the characteristics of its material physical properties, which are ideal for engine materials. Damping and heat conductivity, are though not as good as for gray iron but it has, on the other hand, superior strength [13]. When comparing the material with aluminium, there are studies that show higher power per weight ratio for the CGI engine, with the same performance. This is because, due to its greater strength, the engine can be made with lesser wall thickness [15].

2.2 CGImachiningprocessbehaviour

Cast irons are the foremost common engine material for all manufacturers of heavy trucks. As for machining of all other materials, much information about the machining process behaviour that occurs during cutting of cast irons can be extracted from studying the chip formation during material removal. The chip formation process is the result of the interaction between several factors; tool geometry, tool material, work material as well as the chosen cutting parameters. These factors all contribute to the final component´s surface generated during the chip formation process [16]. It is essential to understand this chip formation process as it is a fundamental parameter that affects the productivity in all component manufacturing [17]. This is therefore also essential when machining CGI.

There are clear differences in the chip formation process when machining gray iron, CGI and ductile iron. As gray cast iron materials contain flake graphite dispersed in a silicon–iron matrix, the sharp edges of the flakes provide a very effective stress riser for the machining loads exerted by the cutting edge. When the shear plane approaches a graphite pocket, cracks start to propagate from the edge of the flake and the iron fractures. The fracture starts at the stress riser and ends in an adjacent pocket until the shear load builds up to the fracture strength of the next stress riser. In CGI, the graphite form is vermicular. When machining CGI, it will shear, as for gray, through a graphite pocket which has the least resistance to shear forces. The round edges of the compacted graphite does not initiate cracks as easy as the sharp edges of the flake graphite in gray cast iron which leads to higher cutting forces when machining CGI. The chip formation during machining ductile iron is similar to the formation during steel machining. The nodules of graphite deforms by the


9

compressive tool loads prior to the chip separation. The matrix does therefore not crack, leading to the formation of a continuous chip over the tool edge [9], [18].

In the following section, a brief introduction to the known parameters affecting CGI machinability will be presented.

2.2.1 Influenceofmicrostructure

The machinability of CGI is strongly dependent of the microstructure of the material. It has been shown in previous research studies that CGI is a material family where combinations of various microstructures span over a wide range [4]. The microstructure affects the material physical properties which influence the machinability parameters. Therefore, it is necessary to investigate the interaction between machinability, material microstructure and material physical properties before CGI successfully can be implemented as engine material. Dawson et al, studied this interaction and showed how the pearlite content and nodularity affected the tool life [13]. It has also been shown in other studies that pearlite content is the foremost important microstructural parameter affecting both the CGI material physical properties and the CGI machinability [19], [20]. The nodularity of the CGI material is also important as it affects the tool wear mechanisms, see Paper E [21].

The components being manufactured in the industry today are rarely plain homogeneous blocks, on which many studies are performed in the research labs. Usually real components have various section thicknesses, holes and slots. This strongly affect the microstructure and therefore also the machinability [19]. E.g., in a cylinder block, which has different section thicknesses, the different cooling and solidification rates during casting lead to an inhomogeneous microstructure [5], [9]. A faster solidification rate, in the thinner sections, leads to a more spheroidal graphite structure, which consequently also increases the tensile strength [22]. Further it also increases the percentage of carbides [23]. Heisser showed that the simulated values for the nodularity were between 12% and 70% in one cylinder block, which was very close to actual inspected values [24]. Regarding the effect of cooling rate on material microstructure, and therefore also machinability, it affects coarseness of the pearlite and could result in a difference of 50 MPa in tensile strength [25]. Such a difference in tensile strength is likely to affect machinability. The microstructure in a complex component could therefore not be considered as homogeneous since the thinner the section the stronger the material [23], [26]. This must be taken into consideration when selecting the proper cutting tool and cutting parameters for the machining of CGI.

2.2.2 Influenceofcarbides

Hard carbide inclusions can drastically reduce the tool life in machining of all types of materials. In machining of CGI, much focus has been put on the carbide promoting element Titanium (Ti). The reason for this is that Ti can increase the magnesium range over which CGI is stable. Ti effectively “poisons” the growth of graphite nodules and extends the plateau toward higher Mg contents [9]. Ti, however, increases the strength of the material, by increasing the percentage of pearlite content [22], but more importantly, it can react with carbon and/or nitrogen in the molten iron and form hard and abrasive inclusions of titanium carbon nitride

10

(Ti(C,N)). These inclusions reduce the machinability significantly [27], [28]. Machining experiments in turning have shown that a slight increase of the trace level of Ti from 0.01% to 0.02% is sufficient to reduce the tool life by 50%, see Figure 3a [27]. In high speed milling (400‐1000 m/min) of CGI materials with different Ti content, Sadik [28] showed that ceramic grades were the best choice for obtaining high productivity rate. However, there are no grades available that efficiently could machine a CGI material with titanium content ≥ 0.05% at this cutting speed, see Figure 3b.

(a) (b)

Figure 3: (a) Tool life in turning of CGI as a function of the trace level of Ti [27]. (b) Tool life in milling of CGI as a function of the trace level of Ti for different tool grades [28].

Carbide promoting elements are also found in the scrap material, used for the casting of new components. The chemical composition of that scrap material is highly important and reflects on the material physical properties. Some elements are however more important than others, from a material physical properties and machinability point of view. Chromium (Cr), Manganese (Mn) and Molybdenum (Mo) have a negative effect on machinability and should therefore be monitored carefully. Scrap material with a low concentration of Cr and Mn is desirable from a machining perspective, it is however expensive to purchase this high quality scrap material to be used for the casting of new cylinder blocks [29]. Mo, on the other hand, is not commonly present in the scrap material. It can however be added in the synthesis of CGI cylinder heads in order to increase the strength of the material at higher operational temperatures, which is crucial for a cylinder head material. Mo also improves the thermal fatigue life of the material. It is therefore important to find the right balance between material strength and machinability so that a high productive manufacturing can be achieved with high quality [5], [30].

2.2.3 Tool wear behaviour, cutting parameters and cuttingtoolsforCGImachining

CGI is an excellent material for truck engines, as mentioned above. Machining of CGI components would however affect the manufacturing lines in a different way, compared to the commonly used gray iron, in terms of productivity and machinability. It is therefore essential to compare the two materials with each other

0

1

2

3

4

5

6

7

8

9

10

0 0,05 0,1 0,15 0,2 0,25

Cut

ting

leng

th [k

m] t

o 3

00μm

flan

k w

ear

Titanium [%]

Carbide turning

250 m/min 150 m/min

0

10

20

30

40

50

60

70

80

90

100

0 0,02 0,04 0,06 0,08 0,1 0,12

Cut

ting

tim

e [m

in]

Titanium [%]

Tool life as function of Ti content in CGI for face milling, vc=700 m/min, ap=2 mm, fz=0.125 mm/tooth, ae=40 mm, Dc=80mm

Uncoated ceramic Coated ceramic Coated carbide

Still very good


11

to see what a change would lead to. Furthermore it should be investigated how manufacturing of CGI components could be optimized.

One clear difference in the machining process behaviour of the two materials is the tool wear behaviour. This was carefully studied by Reuter. He showed that tool wear, when machining CGI, was highly dependent on cutting speed [31]. This is mainly because of the manganese sulphide (MnS) layer which forms, acting as a lubricant and as a diffusion barrier when machining gray iron at high speed. Such a layer is not formed when machining CGI because the MnS content is much lower [32]. The explanation to this is that in CGI, magnesium is added to obtain the desired graphite shape. Magnesium is a very strong sulphide builder which results in magnesium sulphide inclusions rather than MnS inclusions [13]. This is reflected on the tool life. Some investigations indicated that a 50% loss of tool life could be expected at high speed milling of CGI with PCBN inserts (Polycrystalline Cubic Boron Nitride) and a 90% loss of tool life at high speed turning with PCBN inserts [33]. This indicates that machining of CGI is preferably done at lower cutting speed, at least when concerning tool life. When studying the tool wear behaviour more specifically in CGI machining it has been found that abrasive wear of the insert is the dominant wear mechanism in milling at a low range of cutting speed (≤ 300 m/min) [28]. This has also been noticed in other studies [34]. At higher cutting speeds (≥ 600 m/min), Da Silva suggests that adhesive wear is the most dominating tool wear mechanism in milling of CGI [35].

However, the tool wear behaviour also differs for the specific type of CGI material that is being machined. Jönsson found that milling of high pearlitic CGI has a different tool wear behaviour compared to low pearlitic CGI. Figure 4 clearly illustrates the more even wear when machining the high pearlitic CGI. Tool wear development is also different. The high pearlitic CGI material has a more predictable tool life as it has controlled and gradually increasing tool wear, while it is more unpredictable for the low pearlitic material [36].

(a) (b)

Figure 4: Typical wear of the cemented coated carbide insert when milling (a) low pearlitic CGI, (b) high pearlitic CGI [36].

Concerning the cutting parameters that are suited for the machining of CGI, it has been observed that it is always a balance between high productivity and acceptable tool life since the machinability is strongly dependent on the choice of cutting parameters. The machinability of CGI also varies for different types of machining operations and selected cutting tool material. In terms of high performance, when milling CGI at cutting speeds below 300 m/min, cemented carbide grades should be used, in combination with high feed rates and width of cut. Here, the ceramic grade does not provide enough abrasive wear resistance, compared to cemented carbides.

12

The ceramic grade does however give good diffusion wear resistance at high cutting speed (≥ 300 m/min), when the feed and/or the width of cut is small. By increasing the feed and/or the width of cut, the ceramic grade will reduce the tool life to the same level as the cemented carbides, because its ability to deform plastic is very limited, which leads to partial edge destruction [37]. In another study, it has however been shown that carbide grades are preferable to ceramic grades even at higher cutting speed (850 m/min) [38].

2.3 Cuttingtooltemperaturemodelling

During machining, the energy introduced to the process, is to a large extent converted into heat that increases the temperature near the cutting edge. The heat generation affects the momentary thermo−mechanical conditions of the cutting tool–workpiece interface. Often, high temperatures are the direct cause of tool wear and tool failure, especially in machining of cast iron and steel. With these higher melting point metals, the tool is heated to high temperatures as metal removal rate increases and, above certain critical speeds, the tools tend to collapse after a very short cutting time under the influence of mechanical and thermal stresses [39]. Since the cutting temperature distribution is of such great importance for the machining performance, it would be of great interest to predict the temperature field on the tool–chip interface. As limited data are available from experiments due to difficulties to access the tool–chip interface, an appropriate cutting tool temperature model can be used for optimizing the cutting parameters or for the development of new cutting tools. This should be considered for CGI machining.

There are many different methods to model the cutting temperature. The methods have either an analytical or numerical approach. Analytical models where early developed by for example Trigger and Chao [40], and more recently by Ståhl [41]. The Finite Element (FE) method is a type of numerical modelling approach that can be used to obtain the cutting tool temperature distribution. This method has in recent years become the main tool for simulating metal cutting processes [42]. Klocke et al, mean that these FE models have advantages compared to analytical approaches where the mathematical equations which describe the cutting process are so complicated that a solution is no longer possible [43]. There are, however, studies that show the benefit of analytical models. Such a study was performed by Grzesik. He compared one analytically predicted cutting temperature model and one numerically predicted cutting temperature model with the results obtained by thermocouple‐based measurement. It was shown that both the analytical model and the FE model had good comparison with the experimentally measured values [42].

However, some researchers state that neither experimental nor simulated results are yet able to describe the complex cutting process. It is only the combination of simulations and experiments that allows a better description of the cutting process [43]. One method to obtain a better model is by inverse FE modelling where experimental data is used to both validate and calibrate the model. Pujana et al. also mean that the use of experimental data in the FE model reduces the error value from the simulation [44]. The inverse method has been used by Lin [45]. He measured the cutting temperature on the machined surface in milling using an infrared pyrometer, and utilized the results for solving the unknown boundary at the cutting tool‐workpiece interface.

13

3 A MACHINING MODEL FOR CGI MACHINABILITY STUDIES

This chapter presents a machining model which takes into consideration the CGI microstructure, presence of carbide promoting elements and cutting parameters effect on tool life and tool wear mechanisms. Then, tool life is used to evaluate the machinability. The first section of the chapter describes the methods used for evaluating the machinability. This is followed by a section that highlights the influence microstructure has on CGI machinability based on a DoE study, presented in Paper B. In the third section, the effect of carbide promoting elements on CGI machinability is presented. More details about these experiments are found in Paper A. It should be noted that some of the results presented in Section 3.2 and Section 3.3 are not to be found in Paper A and Paper B. The results from these papers have been analysed further. The fourth section demonstrates how the cutting parameters affect CGI machinability. The last section in Chapter 3 deals with machinability of CGI from a process planning perspective.

Compacted graphite iron is to some extent even today used as engine material in the heavy truck industry. But up until now, it has not been as widely used as the more commonly used material for this application; gray iron. One reason for this is its drawbacks in machinability and lack of experience in machining of the material. Knowledge about machining of the material and its machinability is consequently inadequate. For a successful implementation of CGI as engine material it is necessary to obtain deeper knowledge about the material and its machinability.

A CGI machining model was for this reason developed. The machining model is a part of the machinability framework as illustrated in Figure 5.

Figure 5: Machining model as part of machinability.

Figure 5 illustrates the basic concept of the machining model. The microstructure of the CGI materials reflects on the mechanical properties and machinability of the material as studied in Section 3.2 and 3.3. Machinability is affected to a large extent by mechanical and thermal loads generated during the cutting process. Therefore, cutting forces, analysed in Section 3.5, and heat generation, treated in Section 4, are important components in the machining model as they affect tool wear mechanisms and tool life as well as surface integrity of the machined part. The interaction

Tool lifeTool wear mechanisms

Cutting forces

Vibration

Heat generationTemperature distributionCGI material

Mechanical propertiesHardness

Material strengthElastic modulus

Machining operation

Surface roughness

MicrostructureNodularity

Pearlite contentChemical composition

Section effect

14

between cutting process and the elastic structure results in vibrations. Its contribution to the machining model is considered in Section 3.5.

The CGI machining model, presented in this thesis, is based on this framework. The model considers machinability both from a design perspective and from a process planning perspective. The contribution of the CGI physical properties has to be emphasized. High strength of the material, good heat conductivity and high damping, are of course important from a design perspective of a heavy duty diesel engine in CGI. However, in order to achieve high process accuracy and a highly productive component manufacturing it is also important that other parameters are taken into account during the production development process from a design perspective. The material parameters, e.g., microstructure, chemical composition and thickness of the sections have a great effect on the machinability of the material.

Furthermore, the process parameters, e.g., tool material, tool geometry, cutting parameters, fixturing and machine tool characteristics also strongly affect the machinability. These parameters should be considered in the production development process of engines so that in the end, high process accuracy and high productivity may be achieved. Figure 6 illustrates a fundamental concept of which factors affect the machinability from a design perspective.

Figure 6: Illustration of important factors to consider from a design perspective in order to obtain good machinability, high process accuracy and high productivity.

When optimizing the material with regards to machinability, the process parameters are strongly linked to the material parameters. Since they do not only have an individual contribution on machinability, they could also cross‐correlate with each other. One particular cutting tool can, for example, demonstrate a certain correlation with one specific type of graphite morphology, while another sort of cutting tool could behave in a different way. It is therefore challenging, if even possible, to identify the optimal process parameters for certain material parameters. However, by studying the effect different process and material parameters have on

Machinability

Process parameters

Material parametersMicrostructure

Section thickness

Chemical composition

Cutting parameters

Tool material

Tool geometry

Fixturing

Machine tool characteristics

A MACHINING MODEL FOR CGI MACHINABILITY STUDIES

15

the machinability, deeper knowledge about this interaction is obtained. This facilitates future optimization procedures.

The process parameters are also important from a process planning perspective. In this, there are other factors that also affect the machining results and therefore the machinability. The component configuration (geometrical shape), milling cutter positioning with respect to the workpiece, milling cutter diameter and number of inserts, all strongly affect the machinability, especially in regards to tool fracture.

The fundamental understanding regarding machinability of the material can be obtained by studying the influence of material and process parameters. A complete picture of the material machinability in a certain machining operation is however not obtained until it is also seen from a process planning perspective. The machining model developed in this chapter is part of the machinability framework as illustrated in Figure 5. However, there are factors that are not considered in the machining model such as workpiece fixturing, machine tool characteristics and cutting tool (Figure 6). The CGI machining model, however, illustrate the most important aspects of CGI machining.

3.1 Methodtoevaluatemachinability

There are several factors that affect the machinability, as mentioned above. The machinability of the material can furthermore be evaluated by numerous parameters. Tool life, cutting force, surface roughness and chip formation are some examples. The experimental work that has been carried out in this thesis is driven by the needs of the heavy truck industry, and focused on intermittent machining of cylinder blocks and cylinder heads. Surface roughness is not considered in this thesis. This is because the presented experimental work is related to rough machining, where surface finish is not of greatest concern. High process accuracy is of course important in manufacturing of these components but the economical aspect is related to tool life versus material removal rate (MRR). Therefore special attention has been put on tool life. Tool life is also the most widely used machinability criterion [46].

A tool life criterion has been used to acquire the tool life end in all milling experiments, presented in this thesis. Three, evenly pitched, cutting inserts have equipped the milling cutter and the tool life criterion states that tool life end is reached whether the average of the maximum flank wear of all three inserts reaches 0.3 mm, or the maximum flank wear of any two cutting inserts reaches 0.3 mm. There are other tool wear mechanisms that can occur during machining resulting in tool failure, for example plastic deformation, chipping, oxidation or tool fracture. In the milling experiments performed in this thesis, the cutting parameters were selected such that the dominant tool wear mechanism was related to abrasive wear on the flank face of the inserts. Flank wear is also the most desirable type of wear [46] and it has therefore been used as the quantitative response in determining the tool life.

To this it should be noted, that when setting up a machining operation, a stable cutting situation is desirable. From a process planning perspective, stable cutting means controlled and gradually increasing tool wear, resulting in predictable tool life. In this respect it is important to select cutting parameters within a parametric domain where the specific tool wear criterion is enforced. If the tool wear behaviour

16

is predictable it will contribute to a more robust machining process, facilitating process planning in terms of tool change intervals. The goal of all machining experiments, presented in this thesis, has therefore been to obtain a controlled and a gradually increasing tool wear. This motivates the selected tool life criterion. Some problems have been seen with tool fracture during the experiments. However, tool fracture is a non‐desirable tool wear mechanism in component manufacturing as it is impossible to foresee. In these undesirable situations, the machining parameters were corrected and the tests were repeated.

The tool wear investigations have mostly been done with Light‐Optic Microscope (LOM), but also using Scanning Electron Microscope (SEM).

Even if tool life is the foremost important machinability response, some concern in this thesis is also given to cutting forces. Cutting force is one of the few quantitative responses that can be measured during the machining operation which can be used as a basis for further analysis [47]. Cutting forces in milling can be acquired in several ways. The most common method is by a fixed force plate dynamometer on which the workpiece is placed. This enables measurement of the three cutting force components in a fixed coordinate system relative the table. However, this method has its limitations, e.g., with respect to the size of the part that can be clamped. Also, the recorded cutting forces could vary during the machining experiment, since the dynamometer will be affected by the changes of the workpiece weight. Therefore, in the experiments carried out in this thesis, a rotating cutting force dynamometer (RCD) has been used, see Figure 7.

Figure 7: Illustrative picture of the rotating cutting force dynamometer (RCD) used for acquiring cutting forces. KISTLER dynamometer (type 9124B1111).

The dynamometer measures the three cutting force components Fx, Fy, Fz as well as of the momentum Mz and is mounted on the milling cutter. The dynamometer has high rigidity and thus a high natural frequency. An advantage it has over the fixed dynamometer is that the cutting forces can be measured independently of the size of the workpiece and in any spatial position (four or five axis milling).

Fx Fy

Fz

Mz


17

One limitation with both techniques is that the dynamometers will register the sum of the cutting force if more than one insert is engaged in cut simultaneously. The contribution from each insert could be studied with more advanced technique, e.g., as Andersson did [48], if that is of interest. The aim of the cutting force experiments, presented in this thesis, was to identify the differences in average cutting force characteristics. The RCD technique is well suited for this aim.

No cutting fluids have been used in the experiments. Cutting fluid is sometimes used in industry, when milling cast iron, not because it prolongs tool life but mainly because it binds the dust of graphite particles (and keeps it within the machine) and removes the chips from the cutting area. In milling of CGI, it is recommended to avoid the use of cutting fluid. The dust should be taken care of with other means, e.g., using vacuum equipment [49].

In the following sections, the influence of microstructure, carbide promoting elements and cutting parameters, on CGI machinability is presented. These are important parameters, from a design perspective, affecting the machinability. In Section 3.5, CGI machinability is considered from a production planning perspective. There, it will be shown that other parameters, as component configuration, milling cutter positioning with respect to the workpiece, milling cutter diameter and number of inserts strongly affect the CGI machinability. These sections contribute to the presented CGI machining model.

3.2 InfluenceofmicrostructureonCGImachinability inmilling

As part of the CGI machining model, studying the effect of the material microstructure on machinability will reveal, apart from the wear mechanisms and tool life, the influence on cutting force, dynamic phenomena, heat generation and surface roughness of the machined part. The latter is not studied in the thesis but the contribution of the surface roughness to machining model and further to the machinability cannot by any means be neglected. The main results presented in Section 3.2 are taken from Paper B.

Material microstructure is one of the most important material parameters (Figure 6) affecting the CGI machinability [4]. The material microstructure reflects on the material physical properties which affect the machinability, as mentioned in Section 2.2.1. It is important to fully understand the interaction between machinability, material microstructure and material physical properties in order to design a material with the required material parameters. For this reason a preliminary study of microstructure´s effect on CGI machinability was initiated, see Paper D [20]. However, for that study, a special “component like” workpiece was used “Sandvik provkropp 16” which had a complex geometry, resulting in non homogenous microstructure. This complicated the analysis. For that reason, a more careful DoE study was started using homogenous workpieces in order to better distinguish the influences of the different microstructural parameters on CGI machinability.

18

3.2.1 Factorialstudy

Pearlite content and nodularity were chosen as two factors for the DoE study. These material microstructure parameters are known to have great impact on machinability [13]. However, in former studies, the influence of pearlite content and nodularity is studied separately, which neglects important interaction effects that could be present [50].

Furthermore, the section thickness of the cast component affects one other material microstructural parameter, the coarseness of the pearlite, see Section 2.2.1. Thinner sections obtain a shorter interlamellar distance in pearlite which has an effect on the material physical properties [25]. It was therefore believed that it could influence the machinability and was therefore included as a third factor in the DoE study. Three different homogenous workpieces were designed in order to separate the effect of interlamellar distance in pearlite on machinability and material physical properties from the other microstructural parameters (pearlite and nodularity), see Figure 8.

(a) (b) (c)

Figure 8: Workpieces used for the DoE study. The workpieces have the same width and length, 120 mm and 350 mm. The workpieces have different height (a) 80 mm, (b) 46 mm and (c) 26

mm respectively.

A complete factorial experiment was performed with a complete randomized design, using the three material microstructure parameters as factors. Pearlite content was set to three different levels and the nodularity to two levels. The three types of workpieces led to three levels of interlamellar distance in pearlite resulting in eighteen unique CGI materials. One benefit of using this complete randomized design with multiple levels for some factors is that nonlinear effects of can be studied [50].

The cast CGI material was characterized, both regarding microstructural and mechanical properties. More information about the characterization can be found in Paper B.


19

3.2.2 Machiningexperiments

Repeated machining experiments were conducted in order to minimize uncontrolled experimental‐error and to investigate the adequacy of the fitted model [50]. The machining experiments were carried out in dry face milling in a Mazak machining centre, 37.7 kW, with an ISO‐50 taper at which a milling cutter was mounted (model R365‐063Q22‐S15H). The milling cutter was equipped with three coated cemented carbide inserts (R365‐1505ZNE‐KM K20W) evenly distributed, in order to always have one insert engaged in cut. For the milling experiments the following cutting parameters were used: vc = 200 m/min, fz = 0.2 mm/tooth, ap = 3 mm and ae = 58 mm. The cutting data were fixed to these parameters to reduce the number of experiments to be run, and also because the influence of cutting data was not the aim of the experiments. The choice of cutting parameters and selected insert was motivated by the recommendation of truck manufacturers as the first choice in face milling operations on cast iron cylinder blocks in production. These were also recommended by the tool manufacturer. The workpieces were pre‐milled on the top, bottom and sides, in order to remove the hard cast skin, with different microstructure and also to obtain good clamping conditions, which was done by help with a magnetic table to ensure uniform and repeatable clamping.

Tool wear was measured at frequent intervals. Tool life end, which was one of the response variables, was reached according to the tool life criteria presented in Section 3.1. Cutting forces, which represented the other response variable, were measured at frequent intervals using a 4‐component KISTLER dynamometer, see Section 3.1. More information about the machining experiments can be found in Paper B.

3.2.3 Results

A model for predicting the tool life as a result of nodularity, pearlite content and interlamellar distance in pearlite was created based on the results from microstructural characterization, mechanical properties characterization and the machinability results. The main factor, interaction and quadratic effects respectively were studied using DoE software [51].

It could be stated that the effect of interlamellar distance in pearlite on machinability was insignificant. Interlamellar distance in pearlite had nevertheless a slight effect on both material physical properties and machinability but this small effect could not be statistically assured. It is believed that this influence would have been greater if even thinner workpieces would have been used. However, the thinnest workpiece used in this study had a thickness of 26 mm. This is similar to the smallest section on a real cylinder block (which was the reference for this study) on which milling operations is being performed. A model demonstrating the influence of solely pearlite content and nodularity was for this reason created. The model has a R2 value of 0.83 and a Q2 value of 0.80. Figure 9 illustrates the predicted tool life in milling of CGI.

20

Figure 9: Influence of the material microstructural parameters: pearlite and nodularity on tool life in milling of CGI.

Pearlite content has a much more significant effect on tool life in milling than nodularity, as clearly illustrated in Figure 9. The model was therefore used to show pearlite´s effect on tool life for a set value of nodularity of 10%, see Figure 10a.

However, even if pearlite clearly decreases the tool life, it has a positive effect on the strength of the material. It is therefore a compromise between material strength and machinability. A new model to illustrate the pearlite contents´ influence on the ultimate tensile strength was therefore developed, based on pearlite content, nodularity and an interaction effect between nodularity and pearlite. The model has a R2 value of 0.96 and a Q2 value of 0.91 and is presented in Figure 10b.

Pearlite content has a major impact on both the tool life and the strength of the material, as illustrated in Figure 10. E.g., if the pearlite content is increased from 60% to 95%, a 45% loss in tool life could be expected. The material strength is on the other hand increased by 20%.

Further analysis showed that pearlite content also was the microstructural parameter most influencing cutting forces. More details can be found in Paper B.

Tool life [min] in milling of CGI (vc=200 m/min, fz=0.2 mm/tooth)

Nodularity [%]

5 10 15 20 25 30

30

40

50

60

70

80

90 40

50

60

70

80

90

30

40

50

60

70

80

90

100

11040

50

60

70

80

90


21

(a)

(b)

Figure 10: (a) Tool life as a function of pearlite content for a CGI material with 10% nodularity. (b) Ultimate tensile strength (UTS) as a function of pearlite content for a CGI material with

10% nodularity. The dashed lines show the upper and lower 95% confidence interval.

30

40

50

60

70

80

90

100

110

120

20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

Too

l life

in m

illin

g [m

in]

Pearlite [%]

260

280

300

320

340

360

380

400

420

440

460

20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

UT

S [

MP

a]

Pearlite [%]

22

3.2.4 Conclusions

From this DoE study it could be stated that:

Pearlite content strongly affects CGI tool life and cutting force in milling and by this the machinability.

Nodularity, in the rage on CGI (0% ‐ 20%), has a slight influence on the tool life in milling of CGI. It has however some effect on UTS.

Interlamellar distance in pearlite does not seem to affect tool life in milling of CGI or material physical properties as strongly as nodularity and pearlite content.

It is a compromise between high material strength and machinability when selecting the suitable CGI microstructure for the application it is to be used in.

These results contribute to the CGI machining model.

3.3 Influence of carbide promoting elements on CGImachinabilityinmilling

As part of the machining model, the following section deals with the influence of carbide promoting elements on CGI machinability. The motive for this is that carbide promoting elements are present in the scrap material, which is partly used for the casting of new components like cylinder blocks and cylinder heads for the heavy truck industry. The chemical composition of the scrap material is highly important as high levels of carbide promoting elements, such as Chromium (Cr) and Manganese (Mn), reduce the tool life drastically due to carbides. This is discussed in Section 2.2.2. It is therefore preferable, from a machinability perspective, to use scrap material with low levels of carbide promoting elements. This high quality scrap material is however expensive.

One other chemical element that promotes carbides is Molybdenum (Mo). Mo is added in the synthesis of CGI cylinder heads in order to increase the strength of the material at higher operational temperatures, which is crucial for a cylinder head material. Mo also improves the thermal fatigue life of the material [30]. Another chemical element that strongly promotes carbides, and therefore affects the machinability, is Titanium (Ti). The effect of Ti on CGI machinability has been thoroughly investigated in several studies [27], [28].

Since carbide promoting elements have such large influence on the engine from both design perspective and machinability perspective, an extensive DoE study was initiated. For more details, see Paper A.


Cr, Mn and Mo were used as factors in the DoE study. The goal of the experiments was to evaluate how the factors affected both CGI machinability and CGI mechanical properties. The factorial levels can be seen in Table 2.


23

Table 2: Factorial levels for the DoE study.

Factor Level[in wt%]

Cr 0 ; 0.2Mn 0.4 ; 0.8Mo 0 ; 0.1 ; 0.2 ; 0.3

It was assumed that Mo effect on machinability was nonlinear, it was therefore set to four levels. A complete factorial experiment was performed with a complete randomized design resulting in 16 unique CGI materials. In addition to these levels, a centre point was introduced (Mo = 0%, Cr = 0.1% and Mn = 0.6%), this was done in order to observe whether Cr and Mn had a linear relation to material physical properties and machinability. As a result, 17 unique CGI materials with different chemical composition were produced for machining experiments in the study. The same type of workpiece geometry as in Figure 8b was used for casting of the different CGI materials. All cast CGI materials were characterized, both regarding microstructural and mechanical properties.

3.3.2 Carbideparticleevaluation

A study was initiated to verify whether the concentrations of carbide promoting elements were sufficient to result in carbide particles. Figure 11 shows two materials with high concentrations of carbide promoting elements.

(a) (b)

Figure 11: (a) LOM picture of a CGI material at 5x magnification. The white fields are carbide inclusions. (b) SEM picture of a CGI material where the white fields (within the carbide

inclusions) are Mo inclusions.

It is clearly demonstrated that carbide particles (white fields) are present in the materials that have large concentrations of carbide promoting elements. That these concentrations of carbide promoting elements also should result in carbides has also been stated in other studies [52]. It was however found difficult to quantify the amount of carbide particles. It was also hard to differentiate between the different types of carbide particles. Nevertheless, the concentration of carbide promoting elements reflects on the amount of formed carbide particles. Measuring the concentration of carbide promoting elements requires no subjective interpretation

24

(in contrast to quantify the amount of carbides) by the operator and is also more practical as control variable in engine manufacturing, as it is easier to monitor. Therefore it was decided that the concentration of carbide promoting elements was preferred as evaluation parameter.


Repeated machining experiments were conducted in order to minimize uncontrolled experimental‐error and to investigate the adequacy of the fitted model [40]. The machining experiments were carried out in dry face milling in a Mazak machining centre, 37.7 kW, with an ISO‐50 taper at which a milling cutter was mounted (model R365‐063Q22‐S15H). The milling cutter was equipped with three coated cemented carbide inserts (R365‐1505ZNE‐KM K20W) evenly pitched, see Figure 12, in order to always have one insert engaged in cut.

Figure 12: Machining set‐up for milling experiments.

For the milling experiments the following cutting parameters were used: vc = 200 m/min, fz = 0.2 mm/tooth, ap = 3 mm and ae = 58 mm. The cutting data were fixed to these parameters to reduce the number of experiments to be run, and also because the influence of cutting data was not the aim of the experiments. The choice of cutting parameters and selected insert was motivated by the recommendation of truck manufacturers as the first choice in face milling operations on cast iron cylinder blocks in production. These were also recommended by the tool manufacturer.

The workpieces were pre‐milled on the top, bottom and sides, in order to remove the hard cast skin, with different microstructure and also to obtain good clamping conditions. Clamping of the workpiece was done by help of a magnetic table to ensure uniform and repeatable clamping.

Tool wear was measured at frequent intervals. Tool life end, which was the single response variable, was reached according to the tool life criteria presented in Section 3.1.


25

3.3.4 Results

Tool life end was reached in all machining experiments. More detailed results can be found in Paper A. One dominant tool wear mechanism was observed in all experiments, abrasive wear of the flank face of the tool, typically illustrated in Figure 13.

Figure 13: Representative tool wear picture of an insert reaching tool life end characterized by abrasive wear on the flank face.

A model for predicting the tool life as a result of Cr, Mn and Mo was created based on the results from microstructural characterization and the machining results. The main factor, interaction and quadratic effects were studied using DoE software [51]. Results showed that that no quadratic factor effects for Mo could be stated. However, two interaction effects were present, Mo x Cr and Cr x Mn. The model has a R2 value of 0.91 and a Q2 value of 0.87.

Analysis of the results showed that Cr was the foremost important carbide promoting element studied, that had strongest effect on CGI tool life. Figure 14a illustrates the expected reduction in tool life as Cr content increases for a set value of Mo to 0.1% and a set value of Mn to 0.4%. The figure clearly states that, from machining perspective, 0% Cr content is desirable. However, this is not realistic in today manufacturing of engines. The Cr content should nevertheless be as low as possible. E.g., if the Cr content is increased from 0.05% to 0.15% a 25% loss in tool life can be expected. Mn does not affect tool life to the same extent as Cr, which can be seen in Figure 14b.

Mo, can be added in the synthesis of CGI (contradictory to Cr and Mn) to increase the strength of the material at higher operating temperatures. It was however found to have negative impact on CGI machinability. Its effect on tool life was although not as large as Cr but stronger than Mn. Figure 15 illustrates the effect of Mo on tool life as a function of Cr and Mn.

From machining point of view, no Mo should be added when casting CGI, as clearly illustrated in Figure 15. Mo does however increase the strength of the material at higher temperature and it has been shown that the thermal fatigue life will be improve by 313% for a CGI material with 0.23wt% Mo addition [30]. It is therefore a question of achieving balance between material strength and material machinability.

26

(a)

(b)

Figure 14: (a) Cr influence on tool life in milling of CGI for a set value of Mo and Mn to 0.1% and 0.4% respectively. (b) Mn influence on tool life in milling of CGI for a set value of Mo and Cr to 0.1% and 0.05% respectively. The dashed lines show the upper and lower 95% confidence

interval.

25

30

35

40

45

50

0,00 0,02 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18 0,20

To

ol l

ife [m

in]

Cr [%]

Tool life predicted for Cr (Mo=0.1%, Mn=0.4%)

30

32

34

36

38

40

42

44

46

0,40 0,45 0,50 0,55 0,60 0,65 0,70 0,75 0,80

To

ol l

ife [m

in]

Mn [%]

Tool life predicted for Mn (Mo=0.1%, Cr=0.05%)


27

(a) (b)

(c) (d)

Figure 15: Tool life in milling of CGI as a function of Cr and Mn for different concentrations of Mo. (a) Mo = 0%. (b) Mo = 0.1%. (c) Mo = 0.2%. (d) Mo = 0.3%.

Further analysis showed that all carbide promoting elements (Mo, Cr and Mn) affected the material physical properties. Mn had the greatest effect on UTS and hardness, where a large concentration of Mn increased the strength of the material. Higher level of Cr resulted in a more brittle material. More details can be found in Paper A. It should further be mentioned that a patent application have been made based on the results [53].

35404550

Tool life

202530

55

28

3.3.5 Conclusions

The study presented in this section had the purpose of evaluating the contribution of the carbide promoting elements on the machinability of CGI parts. The carbide promoting elements affect the amount of formed carbides, which is an important parameter to consider in the CGI machining model. As tool life and tool wear mechanisms are of great concern in milling of CGI, the machinability is only limited to these factors. The study also demonstrates that the cutting parameters selected result in a uniform and gradual tool wear, characterized by abrasive wear on the flank face of the tool with no sudden tool fracture.

The following conclusions could furthermore been drawn from this study.

Cr has the strongest effect on tool life in milling of CGI and should therefore be monitored carefully when purchasing scrap material.

Mo, which increases the strength of the material at higher operational temperatures, also strongly affects the tool life

If the Cr concentration is increased from 0.05% to 0.15%, the tool life in CGI milling will be reduced by 25%

3.4 InfluenceofcuttingparametersonCGImachinabilityinmilling

The study in this section refers to the influence of cutting parameters on CGI machinability in face milling using coated cemented carbide tools. Cutting parameters are important both from a design and process planning perspective. However, in this section, it is only considered from a design perspective.

Concerning cutting parameters, cutting speed and feed are the two most relevant factors to consider, since they directly affect the material removal rate and tool life, and also because they can be relatively easily changed. Cutting width is more related to the component configuration and the selected tool geometry. Generally, it is advisable from productivity perspective to perform the machining operation in one pass rather than two, meaning that the width of cut is equal to the component width. This is also the case for depth of cut. If surface finish is not a problem, it is better to perform the machining operation in one pass.

There are many different techniques to obtain the optimal cutting parameters with regards to both high material removal rate and long tool life. Some of the early pioneer work in the area was performed by F.W. Taylor in 1907 [54] when he presented the Taylor equation and by B. Colding who in 1959 [55] started the work which resulted in the Colding equation. Since then, much effort has been made throughout the years to develop even better tools/programs for cutting optimization procedures. However, even if the optimal cutting parameters are found after numerous machining experiments, they are only defined for a specific type of machining operation, cutting tool, clamping, etc. A more universal model has greater practical applicability. Such a model should illustrate how the cutting parameters affect machinability, rather than only suggesting “the right” cutting parameters. By doing so, a deeper knowledge about the machining process behaviour is gained. For that reason, a factorial study was initiated. The focus of the study was the effect


29

different cutting parameters have on CGI machinability. These are important inputs to the presented CGI machining model, in this thesis.


As cutting speed, vc, and feed, fz, are the two most important cutting parameters these were used as factors in a DoE study. The goal with the experiments was to evaluate how the factors affected CGI machinability, characterized in tool life. The factorial levels and the test plan can be seen in Table 3. Each factor was set to three levels in order to see whether the effect on machinability was nonlinear. A complete factorial experiment was performed with a complete randomized design resulting in 9 different cutting parameter combinations.

Table 3: Test plan for the DoE study with the corresponding material removal rate (MRR).

Cutting datacombination

vc [m/min]

fz [mm/tooth]

MRR [cm3/min]

1 120 0.15 41.3 2 120 0.20 55.0 3 120 0.25 68.8 4 160 0.15 55.0 5 160 0.20 73.3 6 160 0.25 91.7 7 200 0.15 68.8 8 200 0.20 91.7 9 200 0.25 114.6

A unique “component like” workpiece was design and used for the machining experiments in contrast to the machining DoE studies presented in Section 3.2 and Section 3.3. The workpiece was designed to reproduce a real cylinder block. Thorough microstructural and mechanical properties characterization was performed and the results are illustrated in Table 4. The workpiece will be discussed further, from a process planning perspective, in Section 3.5.

Table 4: Microstructural and mechanical properties of the “component like” workpiece.

Factor ValueNodularity 10 [%]Pearlite content 90 [%]Tensile strength 468 [MPa]Elongation to fracture 1.9 [%]


Repeated machining experiments were conducted in order to minimize uncontrolled experimental‐error and to investigate the adequacy of the fitted model [40]. The machining experiments were carried out in dry face milling in a Mazak machining centre, 37.7 kW, with an ISO‐50 taper at which a milling cutter was mounted (model R365‐125Q40‐S15H). The milling cutter was equipped with three coated cemented carbide inserts (R365‐1505ZNE‐KM K20W) evenly pitched.

For the milling experiments the following cutting parameters were used: ap = 3 mm, ae = 100 mm, vc and fz according to Table 3. Tool wear was measured at frequent

30

intervals. Tool life end, which was the response variable, was reached according to the tool life criteria presented in Section 3.1.

Clamping of the “component like” workpiece was done by help of a magnetic table, see Figure 16. The bottom and top of the workpieces was pre‐milled in order to obtain good clamping conditions and to get the same depth of cut the first cutting pass.

Figure 16: Machining set‐up with the “component like” workpiece.

3.4.3 Results

The results from the machining experiments are illustrated in Figure 17a together with the material removal rate (MRR) for the different combinations of cutting data (Table 3). Another representation of the results is presented in Figure 17b, where the removed amount of material represents the machinability.

There is a large variation in tool life for the different cutting data combinations as can be seen in Figure 17a. The longest tool life was obtained for cutting data combination 3 (Table 3). This combination also has relatively high MRR and therefore the removed amount of material is also large, see Figure 17b. When analysing the results, it is evident that generally, longer tool life is obtained at lower material removal rate. The trend is however nonlinear. Cutting data combination 3 has for example longer tool life as compared to cutting data combination 1, which has lower feed and therefore should result in longer tool life. The tool wear mechanisms were for this reason studied more carefully. It was found that the tool wear pattern differed when combing low feed and low cutting speed, see Figure 18 and Figure 19. At vc = 120 m/min and fz = 0.15 mm/tooth the abrasive wear is concentrated at the nose radius. This explains the nonlinear behaviour in tool life,


31

compared to MRR. Figure 18 also illustrates that at higher cutting speed (200 m/min), the tool wear is not as evenly distributed over the flank face as for lower cutting speed. The dominating tool wear mechanism in this selected domain was abrasive wear on the flank face of the tool.

(a)

(b)

Figure 17: (a) Tool life in milling of CGI with error bars (variation in tool life between the two repetitions) and material removal rate (MRR) for the different cutting data combinations (Table 3). The left vertical scale is tool life (blue bars) and the right scale is the material removal rate (green bars). (b) Same as Figure 17a but with removed amount of material

instead of tool life.

0

20

40

60

80

100

120

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9

MRR [cm

3/m

in]

Tool life [min]

Cutting data combination

Tool life in milling MRR

0

20

40

60

80

100

120

0

20

40

60

80

100

120

140

160

1 2 3 4 5 6 7 8 9

MRR [cm

3/m

in]

Removed amount of material

[cm

3]

Cutting data combination

Removed amount of material MRR

32

0.15 mm/tooth 0.20 mm/tooth 0.25 mm/tooth

120

m/min

160

m/min

200

m/min

Figure 18: Tool wear on flank face, represented by one of the three inserts, for each cutting data combination (Table 3).

0.15 mm/tooth 0.20 mm/tooth 0.25 mm/tooth

120

m/min

160

m/min

200

m/min

Figure 19: Tool wear on rake face, represented by one of the three inserts, for each cutting data combination (Table 3).

A model for predicting the tool life in milling of CGI as a function of vc and fz was created based on the machining results. The main factor, interaction and quadratic effects were studied using DoE software [51]. A model was created based on the main factor effects, two interaction effects and one quadratic effect. This is illustrated in Figure 20. The model has a R2 value of 0.87 and a Q2 value of 0.71.


33

Figure 20: Influence of the cutting parameters: feed and cutting speed on tool life in milling of CGI.

Tool life in milling of CGI is more dependent on cutting speed than feed, as can be seen in Figure 20. This has also been seen in other studies [56]. This is not surprising as it is well known that higher cutting speeds in machining of CGI can lead to looses in machinability [31]. According to Figure 20, high feed rate and low cutting speed is preferable. However, a greater feed leads to a larger chip thickness resulting in increased cutting forces and therefore greater load on the inserts. This increases the probability of sudden tool fracture [47], which also occurred in this study when the feed exceeded 0.25 mm/tooth. The feed has therefore an upper limit for which sudden tool fracture will not appear. This should especially be considered when machining complex components as the inserts are more prone to fracture, in comparison to machining of homogenous workpieces under the same conditions. This will be discussed further in Section 3.5.

A prediction model based on cutting speed was established as it was of such great importance for the tool life in milling of CGI, see Figure 21. If the cutting speed is increased from 120 m/min to 200 m/min, a 50% reduction in tool life could be expected. The MRR is however increased by almost 70%.

Tool life in milling [min]

Cutting feed [mm/tooth]

0,15 0,16 0,17 0,18 0,19 0,2 0,21 0,22 0,23 0,24 0,25120

130

140

150

160

170

180

190

200

60

70

80

90

100110

120

60

70

80

90

100

110

120

60

70

80

90

120

100110

34

Figure 21: Tool life in milling of CGI as a function of cutting speed for fz = 0.2 mm/tooth. The dashed lines show the upper and lower 95% confidence interval.

3.4.4 Conclusions

From this study the following conclusions could be drawn:

vc has larger influence on tool life in milling of CGI than fz.

The dominating tool wear mechanism, in the selected domain, was abrasive wear on the flank face of the tool.

At low feed (0.15 mm/tooth), tool wear is more concentrated near the nose of the insert which reduces the tool life in milling of CGI.

By increasing the cutting speed from 120 m/min to 200 m/min, a 50% reduction in tool life in milling of CGI could be expected. The MRR is however increased by almost 70%.

Good productivity and tool life is obtained with high feed and low cutting speed in milling of CGI.

The inserts showed stronger tendency to fracture when machining the “component like” workpiece, in comparison to the homogenous workpieces.

These results are important inputs to the CGI machining model.

40

50

60

70

80

90

100

110

120

130

120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 200

Too

l life

[m

in]

Cutting speed [m/min]

Tool life in milling as a function of cutting speed for fz=0.2 mm/tooth


35

3.5 Machinability of CGI from a process planningperspective

The process parameters are obviously important from process planning perspective as they directly affect the machining result. These parameters could also easily be adapted for the specific machining operation. There are however other factors that affect the machining results and therefore the machinability, especially in intermittent machining. Other important factors to consider here are the component configuration, milling cutter positioning with respect to the workpiece, milling cutter diameter and number of inserts. These factors should be considered when setting up a machining operation to obtain a stable cutting situation, which is desirable. From process planning perspective, stable cutting means controlled and gradually increasing tool wear, resulting in predictable tool life. In this respect it is important to select cutting parameters in a parametric domain where tool wear criterion is enforced. The main cutting parameters that are crucial in this respect are cutting speed and feed. There are two other unfavourable situations in the machining of real parts.

Selection of too high cutting speed with the result of moving the wear area from the flank face of the tool to the tool‐chip interface on the rake face. Then sudden fracture could occur due to high thermal stresses.

Unfavourable entrance and exits of the cutting edge, resulting in high mechanical stress on the tip of the tool leading to edge fracture.

The second situation is more likely to occur when milling of complex components with holes and slot, e.g., as shown in Figure 22. This leads to an interrupted machining situation where the inserts have multiple entries and exits each revolution, which affects the operational dynamic parameters. This can lead to forced vibrations which could affect the surface roughness but also tool fracture [57]. Machine tool vibration affects not only the surface quality, but also the tool life and production rates [58]. Further, these multiple entries and exits result in increased cyclic thermal and mechanical loads with each revolution, and could lead to thermal cracking and stronger tendency to exit failure [46].

Figure 22: The cylinder block “component like” OPTIMA Sweden workpiece. The dimensions of the workpiece are: 100x200x400 mm.

36

Some of these problems could be solved by changing the positioning of the milling cutter in relation to the component to be machined. It has been found that exit of cut is of far greater importance than entry of cut, from tool fracture perspective, because of the sudden unloading. The tendency is greatest at larger chip thickness, i.e. when the exit angle is near the centre of the milling cutter [47]. Down milling is therefore usually the first choice due to no problematic chip thickness at the end of cut [59]. However, often the situation is more complex. If the width of cut is larger than the radius of the milling cutter, or if the centre of the milling cutter is inside the workpiece, both an up‐milling and down‐milling situation will occur. Furthermore, some components´ width are not constant, as seen in Figure 22, resulting in varying entry and exit angles during the cutting pass. In addition, when cutting over cavities, an unfavourable cutting situation could occur when leaving the cut at maximum chip thickness. It is therefore a complex task to avoid unfavourable cutting situations over the whole cutting pass. Therefore, by positioning the milling cutter in a proper way, a compromise over the whole cutting pass can be achieved. Generally, having the centreline of the milling cutter well inside the workpiece width is considered a good practice for face milling operations under those circumstances. If the tool is to re‐enter in a peripheral shoulder, this often results in severe entry angle conditions which could lead to tool fracture [46].

Another way to improve the cutting situation is by changing the milling cutter diameter or number of inserts. They are also important factors as they affect the static and dynamic loads and therefore they are further related to machine tool capability, such as spindle power.

The influence of component configuration, milling cutter positioning with respect to the workpiece, milling cutter diameter and number of inserts could highly affect the machining results in terms of vibrations, tool fracture and tool life. This is not unique for CGI. However, for CGI, the strength of the material is strongly affected by solidification and cooling rates. This means that the material properties could greatly differ in thin and thick sections. Consequently, it is highly important to carefully plan the machining operation, in intermittent machining of CGI, to obtain a stable cutting situation with controlled and gradually increasing tool wear. The milling operation is in the following sections studied more carefully from a process planning perspective to acquire a deeper understanding of how CGI components could be machined successfully. This gives vital information to the presented CGI machining model in this thesis.

3.5.1 Microstructuralandmechanicalpropertiesevaluation

A “component like” workpiece was developed for this purpose (Figure 22). By designing the workpiece to resemble a real component out in the industry a better correspondence with real machining results will be achieved. This is the approach that should be taken in order to transfer laboratorial results to real industrial applications [60]. The design process of the workpiece focused on achieving a test specimen that had comparable solidification rate, cooling rate, nodularity, and pearlite content to those of a cylinder block. The component configuration of the workpiece is also similar to a cylinder block out in the industry and the performed machining experiments have therefore better correspondence to a real industrial milling application, see Paper F [56].


37

A thorough characterization of the microstructural and mechanical properties of the workpiece was initiated. Five randomly selected cast workpieces were characterized regarding microstructural properties in order to see the variation between the workpieces, but also to see the variation within each workpiece. The microstructure was investigated at three different positions on the workpiece and for each position the microstructure was tested at the surface and at 50 mm depth from the surface. Furthermore, two workpieces were used for the characterization of mechanical properties. The test bars were taken from two different positions. Test bars were also taken from both the surface and at 50 mm depth. The average results with the observed intervals are presented in Table 5.

Table 5: Microstructural and mechanical properties of the workpiece, with inspected intervals.

Factor Mean value IntervalNodularity 10 [%] 7‐16 [%]Pearlite content 90 [%] 85‐95 [%]Tensile strength 468 [MPa] 454‐485 [MPa]Elongation to fracture 1.9 [%] 1.9‐2.0 [%]

It is clear that the microstructure and the mechanical properties are not homogenous in the workpiece. The difference between the inspected workpieces was less than the difference within each workpiece. It was found that the thinner sections demonstrated a stronger tendency to promote spheroidal graphite structure. This corresponds with its faster solidification rate compared to the thicker sections [22], also discussed in Section 2.2.1. The higher strength of the thinner sections is something that should be considered when setting up a machining operation. This since if the tool would leave cut with maximum chip thickness here, it will result in an even larger impact and more undesirable cutting. It is consequently a stronger tendency for the tool to fracture.

It was also found that the nodularity of the thicker sections was more constant with depth from the surface. This is because of the smaller difference in solidification rate, compared to the thinner sections. The nodularity in the “component like” workpiece varied between 7‐16%, see Figure 23. If the nodularity of the workpiece would have been constant, a difference in nodularity between 7‐16% would result in a 10‐15% difference in tool life, according to the tool life model presented in Section 3.2. The “component like” OPTIMA Sweden workpiece is however not homogenous and it is possible that such a difference in nodularity could reflect on machinability in a different way.

The pearlite content was found to be rather constant within the workpiece. Concerning coarseness of the pearlite, it has been found in other studies that the interlamellar distance in pearlite of the thinner and thicker sections are different [19], which can affect the mechanical properties. In the above mentioned study it was found that its effect on machinability could be neglected, at least for sections varying between 26 mm to 80 mm. The thinnest section of the OPTIMA Sweden workpiece is 20 mm and the thickest is 70 mm. The difference in coarseness of the pearlite should therefore not have any significant effect on the machining process behaviour.

The inspected results reflected the microstructural and mechanical properties in a real cylinder block. An even more careful characterization of the microstructural and mechanical properties of the workpieces can be found in Paper B.

38

(a) (b)

Figure 23: Representation of a microstructure with 5% nodularity (a) and 15 % nodularity (b), respectively (source Sintercast).

3.5.2 Cutting force evaluation in interruptedmilling of CGIcomponents

Cutting force evaluation represents an important component in the CGI machining model developed for the present machinability framework, see Figure 5. As generally, the milling process is inherently intermittent, large forced excitations will act on the cutting tool as well as on the entire elastic structure of the machine. These forced excitations induce dynamic effects with unpredictable outcomes on parameters involved in machinability evaluation. Therefore, in order to build a consistent machining model it is important to understand the nature of cutting forces and their effect on machinability. As before the machinability is evaluated here mainly through analysis of tool wear mechanisms and tool life.

A rotating cutting force dynamometer (also discussed in Section 3.1) was for this purpose used. The cutting forces were evaluated while machining the “component like” workpiece illustrated in Figure 22. The aim of the experiments was to investigate in greater depth the influence of component configuration, milling cutter positioning with respect of the workpiece and the number of inserts cutting simultaneously. The workpiece was machined in two cutting passes (vc = 150 m/min, fz = 0.3 mm/tooth, ap = 3 mm and ae = 100 mm), using a face mill (model R365‐125Q40‐S15H) with a diameter of 125 mm. The milling cutter was equipped with three coated cemented carbide inserts (R365‐1505ZNE‐KM K20W). Figure 24 illustrates the cutting operation and the resultant cutting force.


39

(a)

(b)

Figure 24: (a) Cutter position during the first cutting pass. (b) Resultant cutting force as a function of time, for the first cutting pass.

It can clearly be seen that the resultant cutting force varies during the cutting pass. The resultant cutting force alternates from zero to a maximum value, depending on the current chip thickness. This can be more carefully investigated by studying the resultant cutting force during a short time interval (Figure 25c) when the milling cutter is positioned according to Figure 25a. An interrupted cutting situation is evident when the number of inserts engaged in cut alternate from one to zero. Such circumstances can result in forced vibrations which could affect the surface roughness but also lead to tool fracture as seen in Figure 26 [57].

However, the resultant cutting force in Figure 24 has a divergent behaviour at the time interval between 23 and 24 seconds. This is shown in Figure 25d, where the milling cutter is positioned as illustrated in Figure 25b. The resultant cutting force alternates from a maximum value to a value larger than zero. The reason to that is that the next insert starts to cut before the earlier insert leaves cut.

0 10 20 30 40 50 60 70 80 900

500

1000

1500

2000

2500

3000

3500Face milling of CGI, vc=150 m/min, fz=0.3 mm/tooth, Z=3

Time [sec]

Res

ulta

nt c

utti

ng

forc

e [N

]

40

(a) (b)

(c) (d)

Figure 25: (a), (b) The cutter position and the respective resultant cutting force as a function of time (c), (d).

Figure 26: Fractured tool after face milling of CGI with a cutting speed of 150 m/min and a feed of 0.3 mm/tooth.

The machining situation clearly changes during a cutting pass, from a situation with at least one insert in cut, to a condition where the insert starts cutting without the support of the previous insert. Furthermore, this was found to be reflected on tool wear behaviour. The inserts showed a much greater tendency to fracture when machining this ”component like” workpiece, compared to machining of a homogenous workpiece. One explanation for this is that, at some machining instant during the cutting pass over this inhomogeneous workpiece with cavities, alternating entry and exit angles, and multiple entries and exits, there would be

33.1 33.15 33.2 33.25 33.3 33.350

500

1000

1500

2000

2500

Face milling of CGI, vc=150 m/min, fz=0.3 mm/tooth, Z=3

Time [sec]

Res

ulta

nt c

utti

ng

forc

e [N

]

23 23.05 23.1 23.15 23.2 23.25 23.30

500

1000

1500

2000

2500

Face milling of CGI, vc=150 m/min, fz=0.3 mm/tooth, Z=3

Time [sec]

Res

ulta

nt c

utti

ng

forc

e [N

]


41

likely to occur an undesirable cutting situation with maximum chip thickness either at entry or exit of cut. This is highly damaging for the tool. Furthermore, if this undesirable cutting situation occurs when cutting over a thin section in a CGI component, the impact will be even greater as the mechanical strength of the material is strongly dependent on the section thickness, which can increase the tendency for tool fracture even more, as mentioned in Section 3.5.1. The ratio between toughness to hardness of the tool is consequently very important.

The tool fracture tendency should decrease if one or more inserts was always engaged in cut simultaneously, especially at tool entry and exit of cut. In the machining situation discussed above, 80% of the maximum cutter width is used. It is nevertheless only a short time period during the cutting pass that an insert starts cutting with the support from the previous inserts. This time period will increase if a larger number of inserts would be used or if the ratio between width of cut and diameter of the milling cutter would increase.

However, while it is advantageous from tool fracture perspective to have more than one insert engaged in cut at one time, too many inserts cutting simultaneously could result in problems related to power requirements and fixturing. Furthermore the chip evacuation will result in problems if the milling cutter pitch is decreasing. Also from the point of view of regenerative chatter several inserts engaged simultaneously in cutting may result in stability problems due to the coupling of chip thickness variations between consecutive teeth. In machinability studies, an increased number of inserts would also result in larger amount of material to be removed in order to reach the tool life end. Furthermore, even if twice as many insert were to be used, there would still occur situations where the insert starts cutting without the support from the previous insert due to the cavities.

3.5.3 Vibration evaluation in interrupted milling of CGIcomponents

As discussed in section 3.5.2, the intermittent nature of the cutting process induces large dynamic forces at the cutting tool edge as well as in entire machine tool structure. This in turn causes variation of cutting parameters mainly producing a chip thickness variation which to a large extent affects machinability. Apart from a large variation of the cutting force with time during one rotation of the milling cutter which is superimposed on the gradually varying of the cutting force during the movement of one tooth, the cutting force induces high vibration levels in the cutting edge. This dynamic effect causes unpredictable changes in the tool wear mechanism and generally in tool life. More important, the dynamic cutting forces will affect the surface roughness and surface integrity of the machined part due to the relative movement between cutting tool and workpiece caused by vibrations, see Figure 5. Depending on the total numbers of teeth on the milling cutter, the numbers of teeth simultaneously in‐cut and the rotation of the cutter, various dynamic phenomena can be identified. When the tooth‐pass frequency is close to one of the natural frequencies of the machine tool structure, large forced vibrations will occur due to the resonance. This phenomenon will produce dimensional variations of the machined part and tool fracture. When the chip thickness varies between two consecutive teeth, the regenerative chatter is likely to arise. Chatter will cause chipping of the tool edge and a typical vibration pattern on the surface of the

42

machined part. Therefore, studying dynamic phenomena in intermittent machining will contribute to a more reliable machining model being developed within the machinability framework. Further, these machining vibrations need to be controlled as they are a limiting factor for productivity [61].

The machining operation of the “component like” workpiece was for this reason studied more carefully regarding vibration. The milling cutter was positioned according to Figure 24a, and the cutting parameters was the same as in previous experiment (vc = 150 m/min, fz = 0.3 mm/tooth, ap = 3 mm and ae = 100 mm). A three component accelerometer was placed on the spindle to measure its vibration during machining along to three orthogonal directions. The milling cutter was equipped with three, four and six evenly distributed inserts (with a 12 total numbers of possible) in order to see how the number of inserts affected the vibrations. More inserts engaged in cut simultaneously should result in less forced vibration due to decreasing of the variation of cutting force during a tooth engagement. Figure 27 shows the measured vibrations in y‐direction, which is perpendicular to the cutting path.

Figure 27: Vibration amplitude as a function of cutter position (same cutting pass as in Figure 24a) over the workpiece. The red area highlights where the largest vibrations occurred.

The measured vibration amplitude has a different behaviour, as compared to the cutting forces, as seen in Figure 24. Figure 27 clearly illustrates how the vibration amplitude is affected by the alternating entry and exit angles and multiple entries and exits.

0 300 mm 400 mm100 mm 200 mm

I acc

(g)

I

Vibration Y direction – 3, 4 and 6 inserts (fz=0.3mm/tooth , vc=150 m/min)


43

The largest amplitude peaks are found between 60‐80 mm and 145‐180 mm respectively, see Figure 27. These are the sections where the insert starts to cut with maximum chip thickness, due to the positioning of the milling cutter in relation to the workpiece. The lowest vibration amplitude is shown between 90‐110 mm. In that interval, two inserts are cutting simultaneously which to some extent reduces the vibrations. Another interesting observation is that an increased number of inserts, does not directly reduce the vibrations. In the thinnest section (145‐180 mm), there is actually larger vibration amplitude when cutting with six inserts as compared to three. One explanation for this is that the tooth passing frequency increases when using more inserts resulting in that higher vibration modes (natural frequencies) are excited in the machining system structure [57]. This was verified by experimental modal analysis. The phenomenon could to some extent be reduced, if two or more inserts would be in cut simultaneously. However, in this thin section (145‐180 mm) there are not two inserts cutting simultaneously, neither in the six inserts or the three inserts configuration due to the cavities.

3.5.4 Conclusionsandinterpretationofresults

This discussion demonstrates that other parameters, such as e.g., milling cutter positioning with respect to the workpiece, should be considered from process planning perspective, rather than solely cutting parameters in optimization of the machining operation.

The cutting conditions clearly change during the cutting pass, both regarding static and dynamic loads. It should be noted that this type of machining situation is common in component manufacturing. The optimization procedure of cutting parameters, when setting up a new machining operation, should therefore be performed on either real components or “component like” workpieces as machining results performed on ideal homogenous workpieces are not comparable to a real machining situation, especially when machining CGI since it is strongly affected by section thickness. This should also be considered in tool development when recommending cutting parameters for CGI machining. In CGI tool development, the relation between toughness and hardness of the tool is consequently very important.

Furthermore, when setting up a machining operation, the number of inserts and milling cutter positioning should be selected in such a way so as to minimize undesirable cutting situations with maximum chip thickness either at entry or exit of cut especially at thinner sections with high material strength. This is highly damaging for the tool and could lead to tool fracture, especially when machining CGI since it is strongly affected by section thickness. These results contribute to the CGI machining model.

A new generation of tools should be developed under circumstances comparable to real machining situations and not under ideal conditions as when cutting homogenous workpieces.

45

4 A NOVEL METHOD TO STUDY THE CHARACTERISTICS OF THE INTERMITTENT

CUTTING PROCESS

This chapter presents a novel method for evaluation of the intermittent machining process behaviour. The method enables a milling operation to be reproduced in turning application. This simulated method was developed in order to study the temperature distribution on the cutting tool during CGI machining, which forms the base for the machining model and further for the machinability analysis performed in this research. The IR camera technique was used to investigate the temperature field on the insert during intermittent machining of CGI. These results are later used as input data in an inverse thermo−mechanical FE model, presented in Chapter 5.

The contact area on the tool–chip interface in particular is considered to be a very important zone, controlling the mechanics of cutting, and becomes a point of focus for developing a realistic machining model. Cutting forces, temperatures, tool wear rates, and machinability of CGI materials are closely associated with the phenomena governing this region.

There is not possible to experimentally extract from a milling process all data needed to develop a complete machining model. As the information available at the tool–chip interface naturally forms the base for the machining model and further for the machinability analysis performed in this research, it is difficult to access this zone due to the problems related among other things to the rotating tool.

In this respect, one of information missing in the machining model is the heat generation and thereby the temperature distribution on the tool–chip interface. This information will give an understanding of the tool wear mechanisms on rake and flank faces of the tool and will serve as a mean for further optimization of the cutting data and/or tool geometry.

Therefore, after carefully studying the intermittent process, as described in Chapter 3, a novel method and workpiece were designed, in order to make it possible to measure the temperature distribution during an intermittent process with a stationary tool and a rotating workpiece.

4.1 Simulatedmillinginturningoperation

It is difficult to investigate the cutting zone physics that occur during chip removal in milling. Placement of sensors is difficult and often practically undoable due to the rotating cutting tool. Therefore, it is more common to study a continuous cutting process, e.g., turning operations, this is presented in Paper C [62].

However, a conventional turning operation is not comparable to a conventional milling operation for two main reasons. Firstly, turning is a continuous cutting process without interruptions performed with a single tool. This is not the case in milling. The interrupted cutting in milling, leads to cyclic heat generation resulting in thermal chocks on the insert. Secondly, in turning, the chip thickness is theoretically constant. In milling however, the chip thickness is not only affected by the chip

46

generating features in turning (e.g., feed and tool angles), but also by positioning of the milling cutter in relation to the workpiece. The thickness of the chip will vary during the engagement of cut. It is obvious that this will have another impact on heat generation and therefore tool wear, in comparison to a conventional turning application. The conclusions drawn from conventional turning studies can therefore not directly be applied to milling.

A novel method was for this reason developed. The goal of the method was to represent a milling operation, emulated in turning via transposition of the cutting process in milling to turning. This approach opens the opportunity to use devices and sensors used for studying the cutting zone physics in turning, e.g., IR camera, thermocouples, high speed cameras, force sensors or quick‐stop devices. A special workpiece, with unique design, was developed. During cutting, its special design results in a chip shape with varying thickness. This is enabled by an axial displacement of a cylindrical surface that is machined, see Figure 28a. The eccentricity, i.e. the cylindrical surface’s axial displacement relative the rotating axis of the workpiece fixtured in the lathe, gives the chip thickness variation which is illustrated in Figure 28b. The design of the workpiece also enables an intermittent process (as in milling) via reducing the diameter for three quarters of the workpiece geometry.

Workpieces were cast in CGI and machined to the right dimensions. The workpieces were characterized both regarding microstructural and mechanical properties, see Figure 29 and Table 6.

Table 6: Microstructural and mechanical properties of the simulated milling workpiece.

Factor ValueNodularity 4 [%]Pearlite content 75 [%]Tensile strength 385 [MPa]Elongation to fracture 1.8 [%]HBW (10/3000) 196

A special turning tool holder was also designed on which a milling insert was placed (coated cemented carbide insert, R365‐1505ZNE‐KM K20W), as this is designed for an intermittent process. The turning tool holder was produced to resemble the milling tool holder used in the machinability studies (Chapter 3) with the same axial rake angle, γp, and same radial rake angle, γf. It was however not possible to reproduce the same entering angle, κr, due to the design of the workpiece resulting in an end milling operation rather than a face milling operation.

The diameter of the milling cutter, Dc, (as in milling) was reproduced by the diameter of the workpiece. Furthermore, width of cut, ae, (as in milling) was replicated via the axial cutting length, see Figure 28b. The design of the workpiece reproduces a down milling operation as the chip thickness in entry of cut is 0.3 mm reducing to 0 mm at exit.

A NOVEL METHOD TO STUDY THE CHARACTERISTICS OF THE INTERMITTENT CUTTING PROCESS

47

(a)

(b)

Figure 28: (a) Illustration of the simulated milling approach. The workpiece dimensions are 400 mm x Ø130 mm (Ø120 mm). (b) Illustration of the emulated chip cross section (grey arc).

(a) (b)

Figure 29: Microstructure of the CGI material at 30x magnification (a) and 110x magnification (b), respectively.

Workpiece

Chip cross section

Tool

ae, Dc / 2

48

4.2 Experimentalevaluationofthetechnique

The developed simulated milling method was used to study the temperature distribution on the cutting tool during intermittent machining of CGI. The reason why temperature is of such great importance is that the heat generated during cutting affects tool wear, which eventually results in tool failure, especially in machining of cast iron and steel [39]. If the temperature field on the insert can be measured, it can also be controlled, which is important in both tool design and when using the inserts in manufacturing to obtain high process accuracy and high productivity.

Analytical models can be used to predict the temperature field on the cutting tool during machining, but in order to validate these models, experimental measurements needs to be made. One accurate and fast technique to acquire the temperature on the cutting tool is the infra red (IR) camera technique. Commonly, it is used to study the cutting temperature in the tool‐chip interface in orthogonal cutting operations. This was, for example, the method used by M´Saoubi and Chandrasekaran [63]. Often the IR technique is used to verify FE models [64], [65], [66], [67]. Sometimes, the IR technique is analysed solely to measure the temperature in the cutting zone, as Behnam did [68].

In this thesis, the IR camera technique has been used to study the cutting tool temperature field on the rake face of the tool in intermittent machining of CGI. By studying the rake face temperature of the tool, the contribution of the nose radius and depth of cut are also observed, as opposed to if the tool‐chip interface would have been studied. The latter case also requires orthogonal cutting, which is rather rare in real industrial applications. Another advantage with the “rake face approach” is that standard tools can be used.

Another approach that will be taken in this thesis is to use the data obtained from the cutting tool temperature measurements as input data in an inverse thermo−mechanical FE model, see Chapter 5. The data will be used both to validate and calibrate the FE model.

Since the chip covers the cutting zone (highest temperature), it was not possible to register the highest temperature during machining, with this “rake face approach”. It was however possible to measure the temperature in the areas right next to the cutting zone and also the back side of the produced chip, during machining. Furthermore, the intermittent process enabled the possibility to study the temperature field on the insert directly before and after cut.

The emissivity on the rake face of the tool was measured as 0.50. The camera used for the experiments had a resolution of 640x480 pixels and an image frequency of 30 Hz. A macro lens was used to get as close as possible to the cutting insert, resulting in an image focus distance of 75 mm and a field of view of 32x24 mm. Since the camera was so close to the cutting zone, where chips were flying towards the lens, the camera had to be protected. A protective case for the camera was built in steel, in which an over pressure airflow was applied, see Figure 30a and Figure 30b. This reduced the amount of graphite particles penetrating the case. In the front end of the case, a special made coated germanium lens was placed. One side of the lens had a durable diamond like carbide coating (DLC), the other side a high efficiency anti‐reflective (AR) coating which resulted in a transmission coefficient > 89% at a


49

wavelength from 8‐12 µm. The hard surface of the lens reduces the abrasive wear from the chips but also allows infra red radiation to penetrate with only small losses.

(a) (b)

Figure 30: Experimental set‐up for the cutting tool temperature evaluation using IR camera technique.

Cutting forces were furthermore experimentally measured. The goal of the cutting forces evaluation was to determine whether the characteristics of the milling process were reproduced in the proposed approach, both regarding the intermittent process and the varying chip thickness.

Machining experiments were initiated with the overall goal to

evaluate whether the method is comparable to milling, concerning cutting forces,

study the temperature field on the insert in intermittent machining of CGI,

use the results as input data in the thermo−mechanical FE model, presented in Chapter 5.

4.2.1 Cuttingforceevaluation

A cutting experiment of CGI was initiated with the following cutting parameters (in terms of milling); vc = 100 m/min, fz = 0.3 mm/tooth, ap = 3 mm, ae = 64 mm, Dc = 128 mm. The measured resultant cutting force during this simulated milling approach is illustrated in Figure 31a.

50

(a) (b)

Figure 31: (a) Resultant cutting force in the simulated milling operation of CGI, vc = 100 m/min, fz = 0.3 mm/tooth. (b) Resultant cutting force during one engagement of cut.

The intermittent process can clearly be noted. The lesser cutting force in the beginning of cut (1.8 sec, Figure 31a) is explained by the smaller chip area of the first revolution (depth of cut in milling). A more detailed picture of the resultant cutting force during one revolution is demonstrated in Figure 31b. The typical cutting force characteristics of a down milling operation, with large amplitude in beginning of cut decreasing as the chip thickness reduces is clearly seen. Figure 31b can be compared with Figure 25d, in Section 3.5.2. It is evident that the down milling operation successfully was replicated, even if the magnitude of the resultant cutting force is different. The difference in magnitude is explained by the difference in cutting parameters, entering angle, κr, and dynamometer positioning in relation to the cutting zone.

It is apparent that the milling operation successfully can be reproduced, concerning cutting force characteristics, by the proposed simulated milling method.

4.2.2 Cuttingtemperatureevaluation

Each pixel, every image sample, is a measuring point when using the IR camera. In Figure 32, an IR image of the cutting insert is shown before it is engaged into the cut.

The full picture cannot be in focus due to the difference in depth. The focus was therefore put near the cutting zone, as that is the area of greatest interest from a machinability perspective.

Machining experiments were then conducted. Figure 33a shows the insert when it is engaged into the cut with the following cutting parameters (in terms of milling); vc = 100 m/min, fz = 0.3 mm/tooth, ap = 3 mm, ae = 64 mm, Dc = 128 mm. The highest cutting temperature (325°C) can be seen on the back side of the chip. The cutting temperature in the cutting zone is obviously larger.

1.5 2 2.5 3 3.5 4 4.5 5 5.50

20

40

60

80

100

120

140

160

180

200vc=100 m/min, fz=0.3 mm/tooth, Down milling

Time [sec]

Re

sulti

ng c

utti

ng fo

rce

[N]

4.2 4.25 4.3 4.35 4.40

20

40

60

80

100

120

140

160

180

vc=100 m/min, fz=0.3 mm/tooth, Down milling

Time [sec]

Res

ultin

g c

utti

ng

forc

e [N

]


51

Figure 32: IR picture of the rake face of the cutting tool, before machining. The dashed lines illustrate the borders of the insert which are hard to distinguish due to difference in focus.

(a) (b)

Figure 33: IR picture of the cutting tool during cutting (a) and directly after cut (b), respectively.

In Figure 33b, the temperature of the insert directly after cut is shown (0.033 sec after leaving the cut). It is interesting to see that the temperature reduces to less than 90°C directly when the chip is removed. A more detailed analysis of the cutting tool cooling behaviour was made at a lower cutting speed (50 m/min), in order to obtain more sampled images during one cycle. The maximum temperature in the area around the cutting zone was recorded as a function of time, see Figure 34.

Insert

52

There is a fast decrease in cutting temperature directly after leaving the cut, as clearly can be noted in Figure 34. The backside of the chip has a temperature around 300°C. One interesting observation is that the cooling rate of the insert is greater directly after leaving the cut (highest temperature). As the cutting tool cools down to a lower temperature, the cooling rate decreases until the insert is engaged into the cut again.

Figure 34: Maximum temperature registered on the back side of the chip, during six revolutions of cut.

Another interesting observation is that the initial cutting tool temperature (before starting to cut) increases for each revolution. An explanation for this could be the accumulation of the heat during consecutive engagements. The initial temperature should reach thermal equilibrium, if the machining operation would have been prolonged.

It should nevertheless be noted that the temperature in the cutting zone is much higher. One way to acquire this temperature is by orthogonal cutting experiments, but these tests are two dimensional and not comparable with the milling operation. A temperature model is therefore needed.

0

50

100

150

200

250

300

350

5,00 5,50 6,00 6,50 7,00 7,50

Temperature [°C]

Time [sec]


53

4.3 Conclusions The study presented in this chapter has the purpose to add to the machining

model the thermal effects generated in intermittent machining. This information was not acquired during the milling experiments due to difficulties connected to temperature measurement.

The developed simulated milling method can successfully be used as a complement to ordinary milling experiments, for more careful studies of the intermittent cutting process. It accurately demonstrates the same cutting force characteristics as in milling.

The IR camera technique has furthermore been used to show that the cooling rate is more rapid directly after leaving the cut than in the instant directly before starting cut. With the same technique it was presented that the initial temperature (before the insert is engaged into the cut) increases for each revolution.

It is believed that the simulated milling method has good potential to be developed even further and be used in future experiments to better understand the characteristics of the intermittent cutting process.

As some temperature information is still missing from the experiments with simulated milling method, due to the chip hiding the rake face of the cutting edge, an inverse computational model is needed to compute the distribution of the temperature between chip and cutting tool based on the IR measurements on the chip external surface, tool rake face between two cycles and cutting forces.

55

5 AN INVERSE THERMO–MECHANICAL FE MODEL FOR INTERMITTENT MACHINING

OF CGI

The following chapter presents an inverse thermo−mechanical FE model for intermittent machining of CGI. The model is based on the experimental results presented in Chapter 4 and in appended papers. Some input data are taken from literature.

5.1 Thermo−mechanical FE model for intermittentmachiningofCGI

The thermo−mechanical model together with the machining model presented in Chapter 3 and 4 form the overall machinability model which is the goal of this thesis. In this chapter, an inverse thermo−mechanical FE model will be presented, which is a compliment to the machining model with the purpose to obtain the missing information from the latter model. In a future perspective, an improved thermo−mechanical model will certainly contribute to better understanding of the machinability evaluation parameters resulting in optimization of both material design and machining model for the reliable manufacturing of CGI components.

The purpose of the thermo−mechanical model is to provide the temperature and mechanical stress distributions on the cutting edge interface. To develop a consistent inverse thermo−mechanical model some experimental information from the investigations performed in intermittent machining is necessary. This information concerns temperature distribution on the external surface on the chip, cutting forces and their contact areas and shear zone characteristics. In addition, knowledge about tool and tool coating material will improve the predictability. Also, available data on material behaviour at an elevated temperature and at high strain rates is valuable input into the model. Some of this information was missing at the time the model was build, therefore the thermo−mechanical model presented in this chapter is not by any means complete. However, it has the important purpose to describe how new knowledge can be extracted from the model and how this knowledge can be interpreted to contribute to a better understanding of the machinability of CGI materials.

Important factors affecting tool wear are thermal and mechanical load distributions on the insert during machining. It is essential to understand this in order to optimize the machining operation. However, it is difficult to investigate the cutting zone physics during chip removal, especially in milling, as sensor placement is difficult and often practically undoable due to the rotating cutting tool. One way to evaluate the temperature and mechanical loads on the insert in these regions is by FE modelling.

A thermo−mechanical FE model was developed based on the simulated milling method, in order to use obtained experimental results as input data, see Chapter 4. This allows an inverse approach, as the data is used both to calibrate and validate

56

the model. The developed model is the first attempt to evaluate the temperature field and the mechanical load on the insert in intermittent machining of CGI. The aim with the FE model is to present a modelling approach, rather than solely the temperature model itself. The equations for the flow analysis and the temperature calculation are strongly coupled, making a simultaneous solution necessary.

The FE model for intermittent machining of CGI is illustrated in a two dimensional representation of the simulated milling method, based on the machining situation shown in Figure 28b. A 2D representation of a 3D machining situation is however not always comparable due to, e.g., geometrical compatibility. However, this is the first attempt and the FE model will be further developed to 3D. In this model the workpiece is rotating with the same speed as the milling cutters rotational speed, while the cutting tool is fixed. However, the simulated milling method is not directly comparable to a real milling operation as the produced chip is inversed.

The objective of the developed FE model is to compute temperatures and mechanical load distribution on the tool‐chip interface in intermittent machining of CGI. The machining operation corresponds to a down milling machining operation with a chip thickness decreasing from 0.3 mm to 0. The main important time instant is at the first full chip engagement. Therefore, the heat and stress distribution are studied in the first milliseconds´ instant during this engagement.

Generally, the CGI graphite morphology makes the iron sufficiently brittle for machine swarf to break into small chips. Plastic shear is the main mechanism of chip formation. As mentioned above, due to the position of the tool with respect to workpiece eccentricity, two zones of high stress, exceeding the yield stress, and consequently of high plastic deformation will occur. In the zone, A, see Figure 35, at the chip tip, the first contact between tool and workpiece occurs. The second zone, B, is formed gradually along the shear zone as the chip slides along the tool face, see Figure 35. These high stresses, forcing the chip to change the direction, result in a fracture of the chip along the shear zone.

Figure 35: Region with Von Misses stresses larger than 3.8x108 Pa. Time is 0.0315 sec.

B

A

AN INVERSE THERMO–MECHANICAL FE MODEL FOR INTERMITTENT MACHINING OF CGI

57

The high stresses result in a stronger segmentation effect than in an ordinary milling operation, this is illustrated in Figure 36a. Figure 36b shows the produced chips after the simulated milling operation with the following cutting data, in terms of milling, vc = 100 m/min, fz = 0.3 mm/tooth and ap = 3 mm. This cutting data corresponds to the input data used in the FE model.

(a) (b)

Figure 36: (a) Simulation of chip segmentation. (b) Chips formed by simulated milling experiments.

The mechanical model is based on a time dependent FE model, while the temperature is studied in a steady state model. Therefore, the stress distribution can be tracked continuously while the heat distribution is studied at discrete times.

5.1.1 MechanicalFEmodel

The FE models used to solve partial differential equations are usually formulated either in a spatial coordinate system (Eulerian), with coordinate axes fixed in space, or in a material coordinate system (Lagrangian), fixed to the material in its reference configuration and following the material as it deforms. Rewriting the partial differential equations on a freely moving mesh, results in an Arbitrary Lagrangian‐Eulerian (ALE) method. In the special case when the map from mesh coordinates to spatial coordinates follows the material deformation, a Lagrangian method is recovered. Similarly, when the map is an identity map, the ALE method becomes entirely Eulerian. The ALE method is therefore an intermediate between the Lagrangian and Eulerian methods, and it combines the best features of both: It allows moving boundaries without the need for the mesh movement to follow the material.

For this model, the Arbitrary Lagrangian‐Eulerian (ALE) approach was selected. It is a very effective alternative for simulating large deformation problems. In its most basic sense, the ALE method defines that the mesh motion is independent of the motion of the material being analyzed. The mesh model is shown in Figure 37.

Chip fragment

58

Figure 37: Meshed 2‐D model.

The FE model is based on two different meshing concepts. The deformed geometry interface is used to represent the separation of the material and the moving mesh is used to study the deformation of the material as the result of physical load. In moving mesh, the mesh follows the deformation. The work‐hardening characteristics of the material are taken into account in the plasticity model. The frictional conditions are described as shear within a layer of the chip adjacent to the rake face of the tool.

5.1.2 Thermo−viscoplasticFEmodel

A cutting model is developed based on the thermo−viscoplastic FE model to analyse the mechanics of steady state intermittent process. The workpiece is assumed to be a thermo−viscoplastic material and the tool is assumed to be a rigid body. The flow stress is computed as a function of strain, strain rate and temperature. The model can predict the chip geometry and chip‐tool contact.

Generally, the heat sources are localized in three zones at the tool‐chip interface. Mechanical energy dissipated in the shear zone consists of plastic flow energy and, for the most part, that is converted into heat. The second significant source of heating is on the rake face between the sliding chip and the cutting tool face. A tertiary source, frictional heating, not considered here, is between the flank face of the cutting tool and the moving workpiece. For sharp tools, the contact area is very small, resulting in the neglect of this source in most models.

Analytical models provide the temperature rise at the tool–chip interface, which is due to a combination of the shear plane heating of the chip and the frictional heating between the chip and the tool face.

The thermal model presented here takes into consideration the heat generation in the primary zone and secondary shear zone. The heat generation in the primary shear zone is calculated based on the distributions of strain, strain rate and velocity in the primary shear zone. In the secondary shear zone, the heat generation is the result of the superposition of the heat due to shearing forces in the chip adjacent to the contact area tool‐chip, and due to friction forces in the contact area. The heat generated in the primary and secondary zones is used as heat sources in computing the temperature distribution within the tool and chip based on the FE temperature model. As the thermal model is stationary, the temperature distribution is calculated at discrete time interval.


59

The thermal model has the aim of solving the energy equation, in Cartesian coordinates, for the temperature distribution at the tool‐chip interface during intermittent machining. The equation governing the conductive heat transfer processes is the stationary, two‐dimensional energy balance equation

Equation 3

Where K is thermal conductivity, ρ is the density cp is specific heat of the material, T is temperature and is the volumetric energy addition (taking into consideration the width of cut).

The boundary conditions for the thermal model are selected according to following rules.

Fixed temperature T = T0 where T0 is the temperature measured experimentally on the backside of the chip.

Specified temperature T = T∞ where T∞ is the ambient temperature on the boundaries.

Thermal insulation q0 = 0 on the boundaries, where q0 is inward heat flux (W/m2), normal to the boundary.

Specified heat flux, q = k(∂T/∂n), where q is the specified heat flux normal to Sq. k is the specified heat transfer coefficient along Sq and n is the normal vector to the boundary.

Heat losses to the surroundings due to convection or radiation are considered to be negligible. The temperature model boundaries were selected at a sufficient distance from the heat sources in order to minimize the effect of heat generated in the cutting zone.

5.1.3 Results

Material characterization was performed on the workpiece used in the simulated milling experiments, presented in Chapter 4, see Table 7. These results were used as input data for the material model. Furthermore, data obtained from the machining experiments using the IR camera, Section 4.2.2, were also used as input data in the FE model. This is illustrated in Table 7.

Table 7: Experimental input data.

Factor ValueTensile strength 288 [MPa]UTS 385 [MPa]Elastic modulus 145 [GPa]Elongation to fracture 1.8 [%]Hardness 196 [HBW]Tool temperature before entry of cut 90 [°C]Chip temperature at end of cut 325 [°C]

The model is based on a thermo−viscoplastic model for the chip and workpiece where the strain hardening data are extracted from an experimental stress−strain diagram performed on CGI at two different strain rates, see Figure 38.

60

Figure 38: Stress−strain curves for two different strain rates.

Because the cutting process is characterized by high strain rate, in the present simulation the values corresponding to the red curve were considered. The tool is represented as a rigid body. Some material properties, which are considered elementary, were taken from literature, and not presented here.

The model also takes into consideration the cutting parameters used for the simulated milling experiments in Chapter 4, see Table 8.

Table 8: Cutting parameters (in terms of milling).

Factor ValueCutting speed, vc 100 [m/min]Feed, fz 0.3 [mm/tooth]Depth of cut, ap 3 [mm]Width of cut, ae 64 [mm]Tool diameter, Dc 128 [mm]

COMSOL Multiphysics [69] was used to solve the model with the boundary conditions and the presented input data according to Table 7 and Table 8. The model can be used to estimate the mechanical load on the insert and the temperature distribution on the tool during intermittent machining of a CGI material. These are the two most important features affecting tool wear.

The plastic deformation of the chip at the time instant 53.875 ms is illustrated in Figure 39. The figure shows that most part of the chip in contact with the tool is in a plastic deformation state.

Str

es

s [

MP

a]

Strain [%]


61

Figure 39: Plastic deformation of the chip at t = 0.053875 sec. Black areas shows the zones of plastic deformation.

At a cutting speed, vc = 100 m/min, the chip segmentation starts at 0.069645 sec, see Figure 40. Then the process is repeated for thinner chip thickness values until complete removal of the chip from the workpiece for one cycle. The mechanical load and temperature are gradually decreasing with chip thickness.

Figure 40: Chip deformation, von Mises stress [Pa], at the time instant 0.069645 sec, where chip segmentation starts.

The analysis of the stresses on the shear plane shows a non‐uniformed distribution of the shear stress, as shown in Figure 41b at two different time instants. Although, in the earlier time instant, the distribution is rather constant, due to stress exceeding the level of yield stress, the distribution becomes non‐uniformed.

Cuttingtool

Deformed chip

62

(a) (b)

Figure 41: Von Misses stress along the shear plane (dashed line) at the beginning of cut (blue curve) and at t = 0.0543 sec (green curve).

The CGI thermal parameters variation with temperature was determined according to the following equation:

Equation 4

Where K is the thermal conductivity of the CGI material, K0 is the thermal conductivity of unalloyed iron and ∑A is the sum of alloying elements in percentage. The variation of thermal conductivity for CGI is illustrated in Figure 42.

Figure 42: Thermal conductivities of different materials [70].

For the time t = 0.0315 sec, the isothermal lines are shown in Figure 43a. The heat source in the primary zone is calculated for the region with stresses shown in Figure 35. The seizure region at the interface, chip‐tool, is representing by the region A and B in Figure 35, while the heat generated by the friction is considered by the rest of the boundary.

Shear plane


63

(a)

(b)

Figure 43: Isothermal contour plot for two different time instants, (a) 0.0315 sec and (b) 0.05 sec. The black lines illustrate the starting position of the chip.

In Figure 43b, the isothermal lines are shown at t = 0.05 sec. It can be noted that the maximum temperature increase from 708.80 °C to 808.61 °C.

64

5.2 Conclusions

The objective of the model was to explain the thermal and mechanical load distributions on the chip and insert, based on inverse computation. Inputs in the model were the temperature on the external surface of the chip, temperature on the insert between two cutting cycles, material characterization, cutting forces and shear plane angle. The last parameter is obtained from quick‐stop tests. However, in the present research, the cutting force and the quick‐stop results have not been used since at the time of performing the experiments these data were not available.

The model shows good correspondence to the experimentally measured values, considering temperature, although the method is not fully representing of a milling process.

65

6 DISCUSSION AND CONCLUSIONS

This chapter concludes the work presented in the thesis. It also addresses some future research opportunities.

6.1 Discussionandconclusions

The objective of this thesis was to develop a CGI machinability model by identifying and investigating the effect of the major factors and their individual contributions on CGI machining process behaviour. The machinability model in this thesis is based on two sub‐models, a machining model and an inverse thermo−mechanical FE model.

The presented CGI machining model has demonstrated that the microstructural parameters; pearlite content and nodularity, strongly affect both the material physical properties and the machinability. Furthermore, it has been shown that the concentration of carbide promoting elements carefully needs to be monitored as it has great effect on the machinability. The model also illustrates the influence of cutting parameters on CGI machinability. These results have been obtained via full factorial design of experiments studies. It has been demonstrated that this approach has been successful as important cross‐correlation effects, between factors, have been identified. This would not have been possible in a “one factor at the time study” approach. The model clearly illustrates that these material and process parameters should be considered, when designing a material to be used in engine applications.

The presented CGI machining model also demonstrated that the machining process behaviour strongly differs, when machining homogenous workpieces compared to complex components, e.g., as the “component like” workpiece, under the same cutting conditions. The latter case has shown stronger tendency for tool fracture. This is explained by the influence of cyclic thermal and mechanical loads with each revolution, due to the multiple entries and exits for the inserts caused by the cavities, as holes and slots. Another factor that results in the different machining process behaviour for the two cases is the influence of alternating component width. When machining a component with non‐constant width, the entry and exit angles will change during the cutting pass. It has been shown that this leads to unfavourable cutting situation, as entering or leaving the cut at maximum chip thickness, resulting in large impact on the tool. This is highly damaging for the tool and could lead to tool fracture, especially when machining CGI since it is strongly affected by section thickness. From a process planning perspective, this thesis has therefore demonstrated that it is not solely the basic cutting parameters (depth of cut, feed and cutting speed) that should be considered in the optimization procedures of a CGI machining operation. Component configuration, number of inserts cutting simultaneously, positioning and diameter of the milling cutter, are parameters that influence the stability of the cutting process. If these are not set in a proper way, an unstable cutting operation can occur.

66

The presented model in this thesis, consequently demonstrates that the CGI machinability should be considered from both a design and production planning perspective, in order to obtain a highly productive component manufacturing with high process accuracy.

The thesis also demonstrates that complex components cast in CGI clearly have inhomogeneous microstructure. One could say that it is rather a material family than a single material. The cutting tools used for the machining of components in CGI should therefore be able to machine an interval of large range of microstructures, rather than be specialized for just one specific material.

In the thesis, a novel simulated milling method has been presented as part of the CGI machining model. This method successfully reproduces an intermittent machining operation, similar to milling, in a turning application. This facilitates the experimental work as the turning process is easier to study than the milling process due to the rotating inserts in the latter case. With this approach, analysis techniques only formerly used for turning applications, e.g., quick stop tests, can also be implemented in intermittent cutting operations.

A first attempt to build an inverse thermo−mechanical FE model for intermi ent machining of CGI has also been illustrated. The model is used to study the thermal and mechanical load distributions on the chip and insert, based on inverse computation. The results received from the simulated milling experiments, e.g., IR camera measurements of cutting tool temperature, have been used as input data both to calibrate and validate the FE model. The model shows good correspondence to the experimentally measured values, considering temperature, although the method is not fully representing of a milling process.

The CGI material has great potential to be used in several applications where high strength is desired. In the automotive industry, the material physical properties make it ideal as engine material as long as the casting process is robust, resulting in high quality microstructure without a large presence of carbides.

6.2 Futureresearch

In this thesis, CGI machinability has been evaluated from both a design and production planning perspective. However, there are other parameters that affect the machinability of the material which also need to be studied, e.g., the influence of tool material and tool geometries. This is something that should be done in order to obtain a deeper understanding of the machinability of the material.

The developed simulated milling method has great potential to be developed even further in order to study the intermittent process more carefully. One interesting investigation in this application would be to perform quick stop tests. This would make it possible to study the chip formation in milling of CGI. High speed cameras and faster IR cameras could also be used in this new approach as it opens the opportunities for more thorough studies of the intermittent machining process behaviour. The faster and better cameras constantly being introduced on the market make more detailed analyses possible.

The developed inverse thermo−mechanical FE model should be improved. Both regarding the input data (material model, cutting forces, quick stop results) but it

DISCUSSION AND CONCLUSIONS

67

should also be extended in 3D, as shown in Figure 44. The cutting situation in industry is not two‐dimensional and in order to improve the model it should be considered in three dimensions in order to take into account the wear and stress mechanisms in all three cutting zones, i.e. primary, secondary and tertiary zones, respectively.

Figure 44: A 3D representation of the inverse thermo−mechanical FE model for simulated milling.

69

REFERENCES

[1] BIL Sweden. Bilbranschen nr 1 2011.

[2] BIL Sweden. Bilbranschen nr 2 2010.

[3] S. Dawson and T. Schroeder, "Practical Applications for Compacted Graphite

Iron," in Transactions of the American Foundry Society and the One Hundred

Eigth Annual Metalcasting Congress, Rosemont, USA, 2004, pp. 813‐821.

[4] A. Berglund, Characterization of Factors Interacting in CGI Machining (Licentiate

Thesis). Stockholm, Sweden: KTH Royal Institute of Technology, 2008.

[5] M. König, Microstructure Formation During Solidification and Solid State

Transformation in Compacted Graphite Iron (PhD thesis). Gothenburg, Sweden:

Chalmers University of Technology/School of Engineering, Jönköping University,

2011.

[6] I.S.O. Standardization, "Compacted (Vermicular) Graphite Cast Irons‐

Classification," ISO 16112:2006, 2006.

[7] S. Dawson, "Processs Control for the Production of Compacted Graphite Iron,"

in Based on the presentation made at the 106th AFS casting congress, Kansas

city, 2002.

[8] Novacast, www.novacastfoundry.se, August 2011.

[9] G. M. Goodrich, Iron Castings Engineering Handbook. Schaumburg, USA:

American Foundery Society, 2006.

[10] M. Selin, On Thermal Conductivity and Strength of Compacted Graphite Irons

(PhD thesis). Gotenburg, Seden: Chalmers University of Technology/School of

Engineering, Jönköping University, 2010.

[11] V.S.R. Murthy, S. Seshan, and Kishore, "Subsurface Features of Compacted

Graphite Cast Iron Subjected to Wear," Wear, vol. 97, no. 2, pp. 199‐202,

August 1984.

[12] A.M. Pye, "Applications of some of the Newer Cast Irons," Materials & Design,

vol. 3, no. 4, pp. 534‐537, August 1982.

[13] S. Dawson et al., "The Effect of Metallurgical Variables on the Machinability of

Compacted Graphite Iron," in SAE 2001 World congress, Detroit, 2001, pp. 4‐16.

[14] Sintercast, www.sintercast.com, August 2011.

[15] R.J. Warrick et al., "Development and Application of Enhanced Compacted

Graphite Iron for the Bedplate of the New Chrysler 4.7 Liter V‐8 Engine," in SAE

Technical Paper 1999‐01‐0325, Detroit, Michigan, 1999.

70

[16] O. Bayard, Investigation of Forces and Contact Area for Modelling Turning

Processes (PhD Thesis). Stockholm, Sweden: KTH Royal Institute of Technology,

2003.

[17] B. Lindberg, Spånbildningens dynamik ‐ ett steg mot adaptiva

övervakningssystem (in swedish) (PhD Thesis). Stockholm, Sweden: KTH Royal

Institute of Technology, 1986.

[18] G. Georgiou, "CGI High Speed Machine Tool Solutions," in Compacted Graphite

Iron Machining Workshop 2002, Darmstadt, Germany, 2002.

[19] A. Berglund, C. M. Nicolescu, and H. Svensson, "The Effect of Interlamellar

Distance in Pearlite on CGI Machining," in Proceedings of world academy of

science, engineering and technology, vol. 41, Tokyo, 2009, pp. 33‐40.

[20] A. Berglund and C. M. Nicolescu, "Investigation of the Effect of Microstructure

on CGI Machining," in Swedish Production Symposium, Gothenburg, Sweden,

2007.

[21] G. Grenmyr, A. Berglund, J. Kaminski, and C. M. Nicolescu, "Investigation of Tool

Wear Mechanisms in CGI Machining," Int. J. Mechatronics and Manufacturing

Systems, vol. 4, no. 1, pp. 3‐18, 2011.

[22] Y. H. Shy, C. H. Hsu, S. C. Lee, and C. Y. Hou, "Effects of Titanium Addition and

Section Size on Microstructure and Mechanical Properties of Compacted

Graphite Cast Iron," Materials Science and Engineering A, vol. 278, pp. 54‐60,

2000.

[23] R. E. Showman and R. C. Aufderheide, "Controlling Nodularity in Thin‐Wall

Compacted Graphite Iron Castings," in Transactions of the American Foundry

Society and the One Hundred Eigth Annual Metalcasting Congress, Rosemont, Il,

USA, 2004, pp. 823‐829.

[24] C. Heisser and J. C. Strum, "Casting Process Simulation of Compacted Graphite

Iron (03‐025)," in Transaction of hte American Foundry Society and the One

Hundred Seventh Annual Casting Congress, Milwaukee, 2003, pp. 685‐692.

[25] F. Mampaey, "Prediction of Gray Iron Tensile Strength by the Separation of

Variables," AFS Transaction, vol. 97, pp. 879‐897, 2004.

[26] S. Kim, S.L. Cockcroft, and A.M. Omran, "Optimization of the Process

Parameters affecting the Microstructures and Properties of Compacted

Graphite Iron," Journal of Alloys and compounds, vol. 476, no. 1‐2, pp. 728‐732,

May 2009.

[27] W. Guesser, T. Schroeder, and S. Dawson, "Production Experience with

Compacted Graphite Iron Automotive Components," in AFS Transactions 01‐

REFERENCES

71

071, 2001, Reprinted from 2001 AFS Transactions.

[28] I. Sadik, "The Influence of Titanium Content on the Tool Performance in High

Speed Milling of Compacted Graphite Iron," in Sixth International Conference on

High Speed Machining 2007, 2007.

[29] A. Berglund, C.M. Nicolescu, and K. Richnau, "Effect of Carbide Promoting

Elements on CGI Material Processing," in Proceedings of CIRP 2nd International

Conference on Process Machine Interactions, Vancouver, Canada, 2010.

[30] L.V. Diaconu, T. Sjögren, P. Skoglund, and A. Diószegi, "Thermomechanical

Fatigue Investigation of Compacted Graphite Irons," in XXIV. microCAD

International Scientific Conference, Miskolc, Hungary, 2010.

[31] U. Reuter, Wear Mechanism of the Machining of Cast Iron with PCBN‐tools

(Ph.D. thesis). Darmstadt, Germany: Faculty of Mechanical Engineering

Darmstadt University of Technology, 2001.

[32] M. Gastel et al., "Investigation of the Wear Mechanism of Cubic Boron Nitride

Tools used for the Machining of Compacted Graphite Iron and Grey Cast Iron,"

International Journal of Refractory Metals & Hard Materials (UK) 18(6), pp. 287‐

296, 2000.

[33] E. Abele, A. Sahm, and H. Schultz, "Wear Mechanism when Machining

Compacted Graphite Iron," CIRP Annals ‐ Manufacturing Technology, vol. 51,

no. 1, pp. 53‐56, 2002.

[34] A. Berglund and M. Näslund, "Skärbarheten hos Kompaktgrafitjärn," Production

Engineering, Stockholm, Sweden, Research report 2006.

[35] M.B. Da Silva, V.T.G. Naves, J.D.B. De Melo, C.L.F. De Andrade, and W.L.

Guesser, "Analysis of Wear of Cemented Carbide Cutting Tools during Milling

Operations of Gray Iron and Compacted Graphite Iron," Wear, no. 271, pp.

2426‐2432, 2011.

[36] H. Jönsson,Milling of Compacted Graphite Iron (CGI) (Master of Science Thesis).

Stockholm, Sweden: KTH Royal Institute of Technology, 2008.

[37] I. Sadik, "The Interaction between Cutting Data and Tool Performance for

different Cutting Tool Material in Milling of Compacted Graphite Iron," in Sixth

International Conference on High Speed Machining 2007, 2007.

[38] S. Gabaldo, A.S. Diniz, C. L. Andrade, and W. L. Guesser, "Performance of

Carbide and Ceramic Tools in the Milling of Compact Graphite Iron – CGI," J. of

the Braz. Soc. of Mech. Sci. & Eng., vol. Special Issue 2010, Vol. XXXII, no. No. 5,

pp. 511‐517, 2010.

[39] E. M. Trent and P. K. Wright, Metal Cutting, 4th ed. London, USA: Butterworth‐

72

Heinemann, 2000.

[40] K.J. Trigger and B.T. Chao, "An analytical Evaluation of Metal Cutting

Temperatures," Transactions of ASME, vol. 73, pp. 57‐68, 1951.

[41] J‐E. Ståhl, Skärande Bearbetning ‐ Teori och modeller (in swedish). Lund,

Sverige: Lunds Tekniska Högskola, Lunds Universitet, 2009.

[42] W. Grzesik, "Determination of Temperature distribution in the Cutting Zone

using Hybrid Analytical‐FEM Technique," International Journal och Machine

Tools & Manufacture, vol. 46, pp. 651‐658, 2006.

[43] F. Klocke et al., "Examples of FEM application in Manufacturing Technology

120," Journal of Materials Processing Technology, pp. 450‐457, 2002.

[44] J. Pujana, P. J. Arrazola, R. M´Saoubi, and H. Chandrasekaran, "Analysis of the

Inverse Identification of Constitutive Equations applied in Orthogonal Cutting

Process," International Journal of Machine Tools & Manufacture 47, pp. 2153‐

2161, 2007.

[45] J. Lin, "Inverse Estimation of the Tool‐Work Interface Temperature in End

Milling," International Journal of Machine Tools and Manufacture, vol. 35, no. 5,

pp. 751‐760, May 1993.

[46] D. A. Stephenson and J. S. Agapiou, Metal Cutting ‐ Theory and Practice, 2nd ed.

USA: Taylor & Franciis Group, LLC, 2006.

[47] M. C. Shaw, Metal Cutting Principles, 2nd ed. New York, USA: Oxford university

press, 2005.

[48] C. Andersson, M. Andersson, and J‐E. Ståhl, "Experimental Studies of Cutting

Force Variation in Face Milling," International Journal of Machine Tools &

Manufacture, vol. 51, pp. 67‐76, 2011.

[49] B. Isaksson, Senior Manager, Application Development, Sandvik Coromant AB,

2008 AMG presentation (video), Presentation from the Sintercast homepage.

[50] R. L. Mason, R. F. Gunst, and J. L. Hess, Statistical Design and Analysis of

Experiments ‐ With Applications to Engineering and Science, 2nd ed. New

Jersey, USA: John Wiley & Sons, 2003.

[51] Umetrics, Modde version 9.0.

[52] M. Selin, D. Holmgren, and I. L. Svensson, "Influence of Alloying Additions on

Microstructure and Thermal Properties in Compact Graphite Irons,"

International Journal of Cast Metals Research, vol. 22, pp. 283‐285, 2009.

[53] Scania, K. Richnau, F. Wilberfors, and J. Esbjörner, "Method for Determining the

Machinability of a Compacted Graphite Iron," International Application

Number: PCT/SE2010/050950, March 17, 2011.

REFERENCES

73

[54] F.W. Taylor, "On the Art of Cutting Metals," Transactions of the American

society of mechanical engineers, vol. 28, pp. 31‐279, 1907.

[55] B. Colding, A Wear Relationship for Turning, Milling and Grinding ‐ Machining

Economics (PhD thesis). Stockholm, Sweden: KTH Royal Institute of Technology,

1959.

[56] A. Berglund, A. Archenti, and C.M. Nicolescu, "Analytical Modelling of CGI

Machining System Dynamic Behaviou," in The International 3rd Swedish

production symposium, Gothenburg, Sweden, 2009.

[57] A. Archenti and C.M. Nicolescu, "Recursive Estimation of Operational Dynamic

Parameters in Milling using Acoustic Signals," in CIRP 2nd International

Conference on Process Machine Interactions, Vancouver, Canada, 2010.

[58] C.M. Nicolescu, Analysis, Identification and Prediction of Chatter in Turning (PhD

thesis). Stockholm, Sweden: KTH Royal Institute of Technology, 1991.

[59] Sandvik Coromant, Productive metal cutting. Sandviken, Sweden: Idéreklam,

Sandviken, 1997.

[60] R. Woxén, H. Hallendorf, and O. Svahn, Handbok i Verkstadsteknik (in swedish).

Stockholm, Sweden: Bokförlaget Natur och Kultur, 1944, vol. II.

[61] L. Daghini, A. Archenti, and C.M. Nicolescu, "Design and Dynamic

Characterization of Composite Material Dampers for Parting‐off tools," Journal

of Machine Engineering, vol. 10, no. 2, pp. 57‐70, 2010.

[62] A Berglund, G Grenmyr, C. M. Nicolescu, and J. Kaminski, "Analysis of

Compacted Graphite Iron Machining by Investigation of Tool Temperature and

Cutting Force," in 1st International Conference on Process Machine Interactions,

Hannover Germany, 2008.

[63] R. M´Saoubi and H. Chandrasekaran, "Investigation of the Effects of Tool Micro‐

Geometry and Coating on Tool Temperature during Orthogonal Turning of

Quenched and Tempered Steel," International Journal of Machine Tools and

Manufacture, vol. 44, no. 2‐3, pp. 213‐224, February 2004.

[64] V. Dessoly, S. N. Melkote, and C. Lescalier, "Modeling and Verification of Cutting

Tool Temperatures in Rotary Tool Turning of Hardened Steel," International

Journal och Machine Tools & Manufacture 44, pp. 1463‐1470, 2004.

[65] E. G. Ng, D. K. Aspinwall, D. Brazil, and J. Monaghan, "Modelling of Temperature

and Forces when Orthogonally Machining Hardened Steel," International

Journal of Machine Tools & Manufacture 39, pp. 885‐903, 1999.

[66] C. Dinc, I. Lazoglu, and A. Serpenguzel, "Analysis of Thermal Fields in Orthogonal

Machining with Infrared Imaging," Journal of Materials Processing Technology,

74

vol. 198, pp. 147‐154, 2008.

[67] G.M. Pittalà and M. Monno, "A New Approach to the Prediction of Temperature

of the Workpiece of Face Milling Operations of Ti‐6Al‐4V," Applied Thermal

Engineering, vol. 31, pp. 173‐180, 2011.

[68] B. Ghiassi, Evaluation of Temperature Distribution on Carbide Cutting Tools

using IR Technique (Licentiate thesis). Stockholm, Sweden: KTH Royal Institute

of Technology, 2001.

[69] COMSOL, COMSOL Multiphysics version 4.1.

[70] P.A. Green and A.J. Thomas, "Thermal conductivities of different material,"

Trans. of American Foundry Society, vol. 87, p. 569, 1979.

75

APPENDED PAPERS

Paper A Berglund, A., Nicolescu, C.M., Richnau, K., “Effect of carbide promoting elements on CGI material processing”, Proceedings of CIRP 2nd International Conference on Process Machine Interactions, Vancouver, Canada, 2010, ISBN: 978‐0‐9866331‐0‐2

Paper B Berglund, A, Nicolescu, C.M., Svensson, H., “The Effect of Interlamellar Distance in Pearlite on CGI Machining”, ICME 2009: International Conference on Mechanical Engineering, Tokyo, Japan, 2009, ISSN: 2070‐3740

Paper C Berglund, A., Grenmyr, G., Nicolescu, C.M., Kaminski, J., “Analysis of Compacted Graphite Iron Machining by Investigation of Tool Temperature and Cutting Force”, Proceedings of 1st International Conference on Process Machine Interactions, Hannover, Germany, 2008, ISBN: 978‐3‐939026‐95‐2

Paper D Berglund, A., Nicolescu, C.M., “Investigation of the Effect of Microstructures on CGI Machining”, The Swedish Production Symposium, Gothenburg, Sweden, 2007, TRITA‐IIP‐07‐06

Paper E Grenmyr, G., Berglund, A., Kaminski, J. and Nicolescu, C.M., “Investigation of tool wear mechanisms in CGI machining”, International Journal of Mechatronics and Manufacturing Systems, Vol. 4, No. 1, pp. 3–18, 2011, ISSN: 1753‐1039

Documents

Criteria for Machinability Evaluation of Compacted Graphite Iron