Institut of Productionmanagement, · Web viewHigh speed machining offers significant improvements in comparison with classical machining processes. It changes the way of thinking

OPERATION SEQUENCING AS THE DECISION BASIS FOR THE FAST PROCESS PLANNING

Drazen Antolic, Predrag Cosic, Slavko Dolinsek

Mr.sc. D. Antolic, (AD) Production Company, ZagrebProf.dr.sc. P. Cosic, University of Zagreb, FSB, I. Lucica 5, 10000 Zagreb

Prof.dr.sc. S. Dolinsek, University of Primorska, Faculty of Management Koper, Cankarjeva 5, 6104 Koper

Keywords: fast process planning, technological knowledge base, stepwise multiple regression

AbstractVery frequently we must answer on some

important requests for offers, generated for individual or batch production, for example : great number of requested offers for production of products at once, small batches with very rarely repetition, frequently changes of priorities during production, short deadlines of delivery, market demands for approaching prices of the individual or batch production near the prices of mass production etc. Purpose of this work is establish possible connections between sketch features and necessary production times for products manufacturing. Research of the connection between machining time and features of product can give as result regression equations.

1. INTRODUCTION

The experienced process planner usually makes decisions based on comprehensive data without breaking it down to individual parameters. There is no time to analyze the problem. Understanding and a methodical thinking flow will improve the performance of the process planner. Good interpretation of the part drawing includes mainly dimensions and tolerances, geometric tolerances, surface roughness, material type, blank size, number of parts in a batch, etc.

Process planning could be presented like a balance between producing a part meets functional requirements, minimal production time and minimal production cost. Relation between part manufacturing, production time and cost certainly exists but is not always very clear.

The operations defined in process planning have to be put in certain order according to precedence relationships based on technical or economical constraints. Operations sequencing depends on many influences like:

a) nature of the material,

b) general shape of the part,c) required level of accuracy,d) size of the raw material,e) number of parts in the batch,f) possible choice of machine tools, etc.

Forming material removal is a most comprehensive process. There is an infinite number of combinations of machines and tools that will produce the part as specified by the drawing. The recommended process is not only a result of the process planner's experience, but also an outcome of the sequence of decisions made. A wrong sequence of decisions may result in artificial constraints, because if the sequence of decisions were different, the constraints might not have existed.

To achieve the nominated goal for definition of sequencing the operations is very complicated, multi-level, particular problem. Therefore, the expected difficulties in the process of solving this problem can be: pattern recognition, selection of datum, connection between machining surfaces and type of operations, machining tools, tools and positioning and work holding, etc.

Few approaches in sequence operations would be considered in the next chapters. First approach named Matrix method [1] can be described as operations defined by putting in certain order according to precedence relationship based on technical or economical constraints. Shape complexity approach as the second possible approach for production time’s estimation is defined through entropy as a measure of sample randomness [2].

The entropy is expressed as H=-Σp i.log2pi ,

where pi is the probability of a certain outcome (angle change along contour in this case). The ultimate goal is to calculate the shape entropy as a measure of shape complexity. Shape shown in Fig. 7 has the entropy of H=2,052.

Third approach named Variants of process planning [3] can be explain as production time’s estimation. For example, estimation of production times & costs by web application for different

11th INTERNATIONAL SCIENTIFIC CONFERENCE ON PRODUCTION ENGINEERING –CIM2007Croatian Association of Production Engineering, Zagreb 2007

CIM2007 June, 13-17, 2007 Biograd, Croatia

variants of product production were developed [3] (Figure 5). Selected variant of product production is result of product shape (Figure 6), way of tightening (Figure 1), roughness surface and kind of machine tools. Thus, production times and costs are result of observed process planning variant.

Fourth approach named Operation sequencing [4] can be explain as development of original web application by Microsoft .net technology and Flash. The goal was to define simple procedure for definition operations sequencing for every surface of the part. The main criteria was satisfaction of the requested geometrical and dimensional tolerance, roughness, etc. In this paper would be discussed second and fourth approach by more details.

Fifth approach named Basic technological operations [5, 6, 7] can be explain as development of the originall knowledge base of fundamental, the most frequently operations.

What can we put as the characteristics for the previous fourth approaches for possible estimation production times? First, problems with the insufficient generalization level of the used procedure, too complicated calculation, insufficient level of automation of solutions generating in IT application, etc.

Figure 1 . selection of machine tools - case for conical machining

Figure 2. Phase - turning of threads with selection shape part, cutting parameters and times

Figure 3 Contour of a valvet approximated by splines & lines

2. TIMES THROUGH PROCESS PLANNINGVery frequently we must answer on some

important requests for offers, generated for individual or batch production, for example : 1) great number of requested offers for production of products at once, 2) small batches with very rarely repetition, 3) frequently changes of priorities during production, 4) short deadlines of delivery, 5) market

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June, 13-17, 2007 Biograd, Croatia CIM2007

demands for approaching prices of the individual or batch production near the prices of mass production etc.

Very important factor for good company competitiveness on the market is technological flexibility.

For successfull company running a business, necessary condition is existence of process planning for every product in saleable process and activities of evaluation of requests of potential customers. It must be stress that often technological knowledge and speed of process planning would be more important than tehnological level of equipment, skills and knowledge of people who technology realised.

So, we can be faced in practice very often by one of two undesirable cases: a) great amount of used time for definition

process planning of products without agreement of order for production products,

b) signing an agreement without estimated precise machining times/costs necessary for products manufacturing and realization agreed upon products.

xxWe can find solution in basic technological processes with simple and fast process planning with high level of automatization without works of planners (http://ptp.fsb.hr)[1]. (Fig.1, Fig. 2, Fig. 3, Fig. 4)

Figure 4 Example of development sequence operations

Fundamental idea for sequencing operations (Fig. 1, 2, 3, 4) is shape recognition, determination between dimensional & geometrical tolerance with requested process roughness, calculation tolerance and cutting addition and final sequence operation (Fig. 4). Temporary web site is: http://www.igorm.net/studadmin/

Figure 5 Determination of tolerance equivalent

Figure 6 Final solution of sequencing operations

Basic technological processes must give requested date to sales department as the most important date for defining product costs/price and date of delivery. On the other hand, basic tehnological processes can be very useful as the base for detailed process planning or optimization of process planning. We can be faced by few approachs in process planning. For example, definition very precise IF THEN procedure for creation technological knowledge database. Or, we can be faced by use of fuzzy logic and certanities of possible solutions. Or, we can try to solve restricted area of problem by heuristic approach. What can it means? Technological processes are basicly based upon product sketches with adequately dimensions, tolerancing (dimensional and geometrical), surface roughness, batch size, shape and kind of material, heat treatment, requested delivery, disposable equipment, tools, etc. On the other hand, process plans is primary results of planner experience, intuition and decision support. Very often, process planners work under high level of pressure or lack of time.

Purpose of this work is establish possible connections between sketch features and necessary machining times for products

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http://www.igorm.net/studadmin/


manufacturing. Defined hypopthesis says that established connections we can express, except methods of AI, with equations. Established purpose is to define basic process planning with satisfactory precision.

3. FORECASTING OF PRODUCTION TIMES AND SEQUENCING OF OPERATIONS

4. RELATIONS BETWEEN BASIC TECHNOLOGICAL PROCESSES, AND SEQUENCING OPERATION

Process planning is primarily based on workpiece sketch and requested tolerances (dimensional and geometrical), roughness, heat treatment, material, batch size, planner experience and skills, etc.

So, fundamental idea in fourth approach [2] of production time’s estimation is investigation of existence kind of relationship between shape and date from sketch and process type, process sequencing, primary process, way of tightening, selection of tools, machine tools, etc.

The greatest challenge is to establish (or investigate) the most important factors from sketch for useful, easy, fast and very exact estimation of production times. It is necessary in process of offers definition for better estimation terms of product delivery, production times and costs, manufacturing management and last but not the least important, product price.

As one of the first step in our project research, we have defined possible shapes of raw material and 12 basic technological processes. The fundamental idea is to establish parameters of basic technological processes based on sketch features of considered product.

Parameters of basic technological processes can be: shape and kind of raw material (features of

sketch, knowledge base), type of workpiece (features of sketch, shape

and dimensions of raw material),

necessary operations for treatment (features of sketch, expected production time and knowledge base).

operations sequencing (features of sketch, , necessary operations of treatment and knowledge base),

necessary production times (features of sketch based on equations).

So, it have to be establish features of sketch (independent variables), possible dependent variables, size and criteria for sample homogenization (principles of group technology) for analysis of variance and regression analysis.

Basic technological processes must give requested date to sales department as the most important date for defining product costs/price and date of delivery. On the other hand, basic tehnological processes can be very useful as the base for detailed process planning or optimization of process planning. We can be faced by few approachs in process planning. For example, definition very precise IF THEN procedure for creation technological knowledge database. Or, we can be faced by use of fuzzy logic and certanities of possible solutions. Or, we can try to solve restricted area of problem by heuristic approach. What can it means?

Technological processes are basicly based upon product sketches with adequately dimensions, tolerancing (dimensional and geometrical), surface roughness, batch size, shape and kind of material, heat treatment, requested delivery, disposable equipment, tools, etc. On the other hand, process plans is primary results of planner experience, intuition and decision support. Very often, process planners work under high level of pressure or lack of time. Process planner can establish possible connections between sketch features and necessary machining times for products manufacturing. Defined hypopthesis says that established connections we can express, except methods of AI, with equations. Established purpose is to define basic process planning with satisfactory precision.

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5. SKETCH FEATURES AND TECHNOLOGICAL DATE – BASE FOR PRODUCTION TIMES ESTIMATION

Figure xxx

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Figure 8 Relation between tables (Marks of parts, Realized technological processes -, Elements of realized technological processes and procedure)

Figure xxx

FAST PROCESS PLANNING

Material may be expressed by three basic groupes: quality, shape and dimensions. Investigation of the connection between machining time and features of product (through four group of independent variables) can give as result regression equation. All elements of the sample are records for created datebase (Figure 7).

Considered sample consists of original production documentation one metal manufacturing Croatian company. For establishing potential high quality relationship between features of sketch and production time we have to execute two actions. One action can be explain as exploring measures for reduction number of indenpendent variables for egression analysis. Method of analysis of variance [4] (ANOVA procedure) and stepwise multiple

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linear regression (Excel, MatLab) are helpful in process of reduction of number of indenpendent variables.

Figure 8 : Flow chart for model development for time estimation and basic technological operations [2]

The other action was process of sample homogenization (for example, elimination of too big or small value of members of sample).

Shape product dependent variable as the most important criteria were established for 5 different product types. As result of development we have developed 5 regression equations.

Size samples are results of sample homogenization and .query of logical operators (classifiers) for 12 basic technological operations (OTP).(Figure 8).

Analysis of resultsAs the precedence work we have to define

domain borders of independent variables (less than 40), reduction number of variables by correlation/factor analysis and definition type of smoothing curve with high index of determination.

Of course, desired level of generalization in regression analysis would be important indicator for the quality of regression equation. One of the most important problem is process of homogenization of sample of products. Adequate method for this action can be one of methods of group technoogy.

Logical operators during query process in database Access were very helpfull in process of homogenization of sample of products. The other approach was critical analysis values of dependent variables and excluding the extreme values.

As example of multiple linear regression (seven variable) (1), after stepwise multiple regression was selected group of metal rod with 221 parts in a sample.Observed multiple linear regression Y = f(X43, X40, X11, X50, X8, X33, X1) has index of determination R2 = 0,742471 for:X43 residuals. (Figure 9).

Y = machining timeX1 = tolerance external diameter of workpieceX8 = surface roughnessX11 = internal diameter of workpieceX33 =ratio length/diameter of workpieceX40 = complexity of workpieceX43 = superficial area of raw materialX50 = difference of length workpiece and raw material

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Figure 9: Partial regression leverage plot for X43

Y= 36.419+13.649 X43 + 0.099 X40 + 0.459 X11 + 2.023 X50 – 4.080 X8 – 0.655X33 + 0.712 X1.

(1)For different group of values of parts (same

group) with the significant level of homogenity were established 5 multiple linear regression equations.

The future research would be conduct in the way of automatic recognition and joining part to the adequate group of parts (logical operators – classifiers in datebase) .

Research as the second request would include more precise measurement and calculation parts of production times. As the third request would be procedure for estimation multiple linear regression with the least variables, the greatest index of determination and good coincidence calculated and predicted values of dependent variable.

Research work would be continued by looking for adequate model for optimization (minimum of machining time). Implementatioin of the genetic algorithm can be one of possible methods for solving optimization problems.

Figure xxx

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Figure xxx

6. ANALYSIS OF RESULTSAs the precedence work we have to define

domain borders of independent variables (less than 40), reduction number of variables by correlation/factor analysis and definition type of smoothing curve with high index of determination.

Of course, desired level of generalization in regression analysis would be important indicator for the quality of regression equation. One of the most important problem is process of homogenization of sample of products. Adequate method for this action can be one of methods of group technoogy.

Logical operators during query process in database Access were very helpfull in process of homogenization of sample of products. The other approach was critical analysis values of dependent variables and excluding the extreme values.

As example of multiple linear regression (seven variable), after stepwise multiple regression was selected group of metal rod with 221 parts in a sample.

Observed multiple linear regression Y = f(X43, X40, X11, X50, X8, X33, X1) has index of determination R2 = 0,742471 for:X43 residuals. (Fig. 9)

Y = machining timeX1 = tolerance external diameter of workpieceX8 = surface roughnessX11 = internal diameter of workpiece

X33 =ratio length/diameter of workpieceX40 = complexity of workpieceX43 = superficial area of raw materialX50 = difference of length workpiece and raw material

Figure 9 Partial regression leverage plot for X43

Y= 36.419+13.649 X43 + 0.099 X40 + 0.459 X11 + 2.023 X50 – 4.080 X8 – 0.655X33 + 0.712 X1.

For different group of values of parts (same group) with the significant level of homogenity were established 5 multiple linear regression equations.

The future research would be conduct in the way of automatic recognition and joining part to the adequate group of parts (logical operators – classifiers in datebase) .

Research as the second request would include more precise measurement and calculation parts of production times. As the third request would be procedure for estimation multiple linear regression with the least variables, the greatest index of determination and good coincidence calculated and predicted values of dependent variable.

Research work would be continued by looking for adequate model for optimization (minimum of machining time). Implementatioin of

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the genetic algorithm can be one of possible methods for solving optimization problems.

7. CONCLUSIONHypothesis about relationship from one

side between sketch features and from the other side production times and parameters of technological processes is confirmed. Result of research is fact that possible initial shape of material raw can be automatic defined on the base of the sketch features.

Process of the previous classification parts in defined types of parts based primarily on geometric features is not so important in the process planning. Solution can, indeed, find not in determination type of part but in parts joining to specific, in advance, type of defined fundamental technological processes (OTP) based on sketch features.

ACKNOWLEDGEMENTSThis project is a part of the scientific

projects (2007-2009) titled Process Production Impacts t to the Competitive and Sustainable Development 120-1521781-3116 financed by the Ministry of Science and Technology of the Republic of Croatia and project supported by Slovenia-Croatia Cooperation in Science and Technology, (2007-2008) named Virtual Manufacturing – Step to Competivity and Sustainable Development financed by the Ministry of Science and Technology of the Republic of Croatia and Slovenian Research Agency (ARSS). We express gratitude for the financial support for these projects.

8. REFERENCES[1] http :// ptp . fsb . hr [2] Cosic, P., Levanic, A., 2004, Web oriented

database system for process planning, Pacific Congress on Manufacturing and Management, PCMM) 2004, 8, - 10 december 2004 - Gold Coast, Australia, ISBN 0-9578296-1-2, 2004, pp 922-928.

[3] Balic, J., Veza, I., Cus, F., Advanced Production Technologies (in Croatian & Slovenian language), FESB, Split & Faculty for Mechanical Engineering, Maribor, 2007, Chapter 4. P. Cosic, Process Planning in Web Environment, ISBN 86-435-0777-6; 2007, pp.59-97.

[4] Volarevic, N., Cosic, P., Improving process planning through sequencing the operations, AMST’05,CISM Courses and Lectures – No. 486 , Springer Verlag, Wien New York, 2005, pp. 337-347.

[5] Volarevic, N., Cosic, P., Shape Complexity Measure Study, DAAAM 2005, Opatija, Croatia, 2005, pp 375-376.

[6] D. Antolic, Estimation of Production Times of Products by Help of Regression Models, Master thesis, defended 27 April 2007., University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2007.

[7] P. Cosic, D. Antolic: ''Fast Process Planning – One of the Criteria for Better Competitiveness'', Ref. number 778, rad objavljen u zborniku, Global Conference on Production and Industrial Engineering (CPIE-2007), 22-24th March, 2007, Jalandhar, Punjab, 144011, India.

[8] P. Cosic, D. Antolic: ''Features of the sketch – Base for the Fast Process Planning'', Ref. number 0105, rad prihvaćen za objavu u zborniku, PSU-UNS International Conference on Engineering and Environment – ICEE – 2007, Phuket May 10 -11, 2007

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T-28 Tablica regresijskog modela za procjenu vremena izrade proizvoda 01-01

REGRESIJSKI MODEL A00B1GRANA OTP-a A00B1 OKRUGLE ŠIPKE

1 Uvjeti klasifikacije A0000 AND ZN05 Like »Okrugla šipka»2 Značajno vrijeme grane

OTP-a -

ZAVISNE VARIJABLE Oznaka tA00B1 A00B1 A00B1 A00B1

1 Minimalna vrijednost min 6 -2 -30 -253,67%

30,44%2 Maksimalna vrijednost max 113 122 52 120,12%

3 Prosječna vrijednost 42,67 42,67 0 14,09%

4 Standardna devijacija 25,62 22,08 12,99 47,02%

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Koeficijent vremena

5,82

4,617 2,77

8 4,61

NEZAVISNE VARIJABLE KOEFICIJENTI JEDNADŽBE Varijabla min max

Slobodni član 55,46511 X45 mM 0,0008 2,66 22,4332 X40 SOK 3 57 1,162213 X11 I 0 75 0,4301074 X50 L 0 18 1,607485 X8 SH 6 13 -5,408816 X18 NG 0 6 -3,260417 X42 H 0 7 1,78711

KOMENTAR NEZAVISNIH VARIJABLII u ovom modelu pretežito su zastupljene složene varijable.X11 - unutarnji promjer izratka zauzima značajno mjesto budući se radi o rotacijskim dijelovima Hrapavost je dvostruko zastupljena, kao osnovna X8 i razlika osnovne i zahtijevane X42, što ukazuje na značaj hrapavosti.Smjer (predznak) koeficijenata je očekivan.X18 – vrijedi isto kao u modelu A0000.

REZULTATI MODELA

VARIJABLA r2 Objašnjeno Greška F p Uzorak

1 7 0,74285 0,733146 13,206 87,4886 0 220 30,95%

KOMENTAR REGRESIJSKOG MODELAModeliranje je izvršeno postupkom unaprijed. Potpuni model (bez ograničenja na 7 nezavisnih varijabli) imao bi 9 uključenih varijabli sa r2 = 0,754414 i RMSE= 12,97.Od 9 varijabli koje su činile potpuni model, iz jednadžbi su izostavljene dvije, i to:X1 – red tolerancije vanjskog promjeraX26 – površina crteža

Model je sličan modelu A00B1, što je očekivano budući da predstavlja 72,85% osnovnog uzorka.

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6. CONCLUSIONHigh speed machining offers significant improvements in comparison with classical machining processes.

It changes the way of thinking on cutting process, cutting tool design and design of machine tool. . . .

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a) Up milling b) Down milling

Figure 1. Peripheral up (conventional) and down (climb) milling

REFERENCESCite the references in the body of the paper using the number in square brackets [1]. All references listed must be cited, and all cited references must be included in the reference list. The format for references is as follows: Last name, initial, year of publication, full paper title, journal name, volume, first and last page. Use only common abbreviations in journal names. Reference numbering style : ( Arial, 10 pt.) , like in sample below

[1] Cebalo, R., Schulz, H., Udiljak, T., 1997, With high speed machining towards 21 st century, 4th International Conference on Production Engineering CIM'97, Zagreb, p. 5-17.

[2] Abele, E., Kluge, J., Näher, U., 2006, Handbuch Globale Produktion, Hanser Fachbuchverlag.

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Institut of Productionmanagement, · Web viewHigh speed machining offers significant improvements in comparison with classical machining processes. It changes the way of thinking