Machinability of austenitic stainless steel SS303

Machinability of austenitic stainless steel SS303

D. O’Sullivan*, M. CotterellDepartment of Mechanical and Manufacturing Engineering, Cork Institute of Technology, Bishopstown, Cork, Ireland

Abstract

Stainless steel SS303 is a grade of material widely used in the manufacture of proprietary inserts for the electronics and automotive industry.

Users have often reported machining difficulties with this material and very little information on its machinability can be found. Problems

such as poor surface finish and high tool wear are common. Optimum setting of machining parameters, such as cutting speeds and feed rates, is

critical with this material, especially in today’s high volume production environment. Machining data from machine tool manufactures,

material suppliers and cutting tool suppliers is not consistent and does not give reliable results when tested in practice. Third party data, from

engineering handbooks, is out of date and is not representative of modern grades of material and tooling. Many of the current problems are

attributed to work hardening of the material during machining, and a trial and error approach is adopted on the shop floor to avoid the

conditions that lead to this phenomenon.

Better scientific understanding of the mechanisms that contribute to workpiece surface integrity and to tool wear when working with this

material is desirable. As a result, research was undertaken to develop some fundamental guidelines on the machinability of this grade of

stainless steel. In the interest of reducing manufacturing and production costs, an on-line technique will be developed for the detection of work

hardening of austenitic stainless steel SS303 in unmanned machining operations. A review of current on-line work hardening detection

techniques is presented. # 2002 Elsevier Science B.V. All rights reserved.

Keywords: Austenitic stainless steel; Machinability rating; Work hardening

1. Introduction

The austenitic stainless steels represent the largest group

of stainless steels in use, making up 65–70% of the total for

the past several years [1]. The austenitic alloys used most

often are those of the AISI 300 series. Users have often

reported machinability problems with this grade of material.

These problems have been attributed to the work hardening

of the material during machining operation.

Machining costs are determined mostly by the time,

which is needed for measuring and machining. Demands

for higher productivity and a better use of cutting tools lead

to a combination of machining parameters, where damage to

the workpiece surface, sub-surface and cutting tool are not

reliably avoided. A fast detection of the formation of work

hardening on the material surface in machining is desirable.

As a result, an on-line technique will be developed for the

detection of work hardening in the workpiece material

during metal removal operations.

It is widely accepted that work hardening of stainless

steels is due to a martensite formation. Martensite may form

in austenitic steels during plastic deformation from working

(mechanical) or due to temperature effects (thermal). Two

types of martensite can form: e-martensite, which forms on

close-packed (1 1 1) planes in the austenite and has a

hexagonal close-packed (h.c.p.) crystal structure; and

body-centered cubic (b.c.c.) a0-martensite, which forms as

plates with (2 2 5) habit planes in groups bounded by faulted

sheets of austenite on (1 1 1) planes [2].

The formation of martensite from austenite can occur

by:

1. g ! e-martensite transformation [3];

2. g ! a0-martensite directly [4];

3. g ! e ! a0-martensite [5–7].

An investigation into work hardening detection techniques is

presented. Some of the specifications for the modern manu-

facturing industry for this on-line technique include: it should

be non-destructive, thus increasing speed and reducing cost of

experimentation. This technique should be readily adapted for

drilling and turning machining centers. It should indicate to the

machine operator when work hardening of the material begins.

2. Review of on-line work hardening detectiontechniques

In production engineering, various techniques are used

to check the integrity state of a machined workpiece, to

Journal of Materials Processing Technology 124 (2002) 153–159

* Corresponding author.

E-mail address: [email protected] (D. O’Sullivan).

0924-0136/02/$ – see front matter # 2002 Elsevier Science B.V. All rights reserved.

PII: S 0 9 2 4 - 0 1 3 6 ( 0 2 ) 0 0 1 9 7 - 8

monitor the process itself or to evaluate the condition of the

cutting tool. In the past, a fast and quantitative inspection of

the surface integrity state in the production line was not

possible. Today, macro- and micro-geometric differences in

the quality of components can be easily controlled by visual

and tentative processes, as well as post-process, process-

oriented and in-process. Fig. 1 shows corresponding systems

available for many applications, which are available. Post-

process means that inspection is only possible after machin-

ing. In-process describes the sensors which can be used

during machining. Process-oriented means that after

machining, the geometry and the surface integrity can be

inspected very easily and quickly.

An on-line method of examination enables the optimiza-

tion of machining conditions. Machining costs are deter-

mined mostly by the time, which is needed for measuring

and machining (see Fig. 2). Manufacturing with in-process

sensing means that no additional time for measurement is

needed. Karpuschewski [8] estimates this reduction in pro-

duction costs to be up to 20%.

The use of process-orientated and in-process micromag-

netic surface and sub-surface non-destructive analysis

techniques are being increasingly used by researchers

[9,10].

In this paper, the principles and measuring results of

different micromagnetic sensors, and acoustical analysis

Fig. 1. Methods for quality inspection [8].

Fig. 2. Advantages of using on-line micromagnetic tests for in-process measurement [8].

154 D. O’Sullivan, M. Cotterell / Journal of Materials Processing Technology 124 (2002) 153–159

systems for the on-line measurement of work hardening in

austenitic stainless steels are presented.

3. Micromagnetic and magnetic investigations ofstainless steels

3.1. Magnetic properties of austenitic stainless steel

All austenitic stainless steels are paramagnetic in the

annealed, fully austenitic condition. The h.c.p. e-martensite

is paramagnetic in contrast to the b.c.c. a0-martensite, which

is strongly ferromagnetic (hard magnetic) and the only

magnetic phase in the low-carbon austenitic stainless steels.

Therefore, work hardened austenitic stainless steels have

detectable magnetic properties that can be eliminated by

annealing.

Quality control of machined workpieces in relation to

residual stresses, hardness and texture is possible with

micromagnetic analyzing systems. The principle techniques

used to date are discussed.

3.2. Magnetic permeability tests

Definition of magnetic permeability [11]: a dimension-

less parameter expressing the ease by which a material

can be magnetized. The ratio of induction to magnetizing

force.

Magnetic permeability tests can be used to identify the

ferrite content of austenitic and duplex grades of stainless

steel. Ferrite content has a significant effect on mechanical

and corrosion properties of austenitic stainless steels. These

magnetic tests are accurate and can quantify the ferrite

content. They are also non-destructive. Portable probes

can measure ferrite contents between 0 and 80%.

3.3. Mossbauer spectroscopy

Mossbauer spectroscopy is an accurate and reliable mea-

suring technique for determining the ferromagnetic/para-

magnetic ratio of alloys [12].

Dictionary definition of Mossbauer spectroscopy: Moss-

bauer spectroscopy is concerned with observing the small

shifts in nuclear energy levels in response to the resonant

absorption and emission of g-rays. Energy can be added to

the system by the Doppler effect and can be used in the

qualitative analysis of around 42 distinct elements, but

mostly for iron and tin compounds.

Meszaros et al. [13] uses a conversion electron Mossbauer

spectroscopic technique to determine the volume of ferro-

magnetic a0-martensite in deformed austenitic stainless

steel, and this was used to calibrate the energy measurement

results of Barkhausen noise (BN) measurements. Measure-

ments were then made on different specimens and results

from the Mossbauer and BN were found to be in very good

agreement with each other.

3.4. Magnetic etching

Magnetic etching is done with the help of a magnetic

solution of colloidal particles to see the morphology and

distribution of the magnetic phase (a0-martensite) in the

specimen. This is conducted by applying the magnetic

solution to the polished specimen surface and observed

microscopically. A cover slip is used to prevent evaporation

of the fluid and the magnetic particles are allowed to settle

for a period of time on the polished surface. The pattern of

the settled particles can then be photographed with a mag-

netic field in ‘‘off’’ and ‘‘on’’ conditions. In the ‘‘off’’

condition, the particles are settled randomly as these are

not affected by any magnetic field. In the ‘‘on’’ condition,

the settled particles are attracted towards the magnetic phase

present on the steel samples under the influence of the

magnetic field. This enables observation of the preferential

attraction of the colloidal magnetic particles towards the

magnetic phase present on the polished surfaces of the

stainless steel samples in the ‘‘on’’ condition.

3.5. Barkhausen noise

BN analysis or micro-magnetic testing is based on induc-

tively detecting a noise-like signal generated in ferromag-

netic materials subjected to alternating external magnetic

field. Magnetic domain walls are forced to move back and

forth by the exciting magnetic field. Pinned to crystal lattice

defects and dislocations, they will jump further only once

forced by sufficient excessive energy of the magnetizing

field. Each such jump will generate a pulse in a coil placed

near the surface of the sample. Pulses generated in a finite

volume of material close to the coil will form a noise-like

signal called magnetic BN, called after Professor Heinrich

Barkhausen, who first discovered this phenomenon in 1919.

Some of the practical applications of BN applications

include: evaluation of residual stresses; evaluation of micro-

structural and hardness changes; testing surface defects,

processes and surface treatments that may involve changes

in both stresses and microstructure.

Meszaros et al. [13] uses magnetic measurements to

characterize the amount of a0-martensite due to room-tem-

perature plastic tensile loading of austenitic stainless steel.

The effects of cold work and annealing heat treatments of the

steel were explored using magnetic BN measurements.

Fig. 3(a) and (b) shows the elongation of SS304 at a very

slow rate (1 mm/min). As can be seen, the BN energy

increased with increasing elongation. The BN energy was

found to be linearly proportional to the amount of a0-martensite—which has lead to the hardening of the material

from 150 VHN (0% strain) to 360 VHN (50% strain).

Fig. 4(a) and (b) shows the variation in the BN energy and

hardness values as a function of temperature. As can be seen,

the BN energy started to decrease at about 350–400 8C and

reached a zero level at about 600 and 700 8C, respectively. It

shows that the decrease in hardness is due to the disappear-

D. O’Sullivan, M. Cotterell / Journal of Materials Processing Technology 124 (2002) 153–159 155

ance of the ferromagnetic phase, namely a0-martensite,

because at this temperature the reverse transformation of

strain-induced martensite to austenite has completed.

In this research, the use of BH measurement was found to

be a very useful non-destructive and quantitative way to

characterize the amount of a0-martensite phase in austenitic

stainless steels. Even though the BH method seems to be a

good analysis technique, little work in this area has been

completed, so an uncertainty about this method still remains.

Also, the amount of e-martensite, though not as significant,

cannot be detected or quantified by this method.

4. Acoustic analysis systems

4.1. Introduction

Acoustic emission (AE) can be defined as the transient

elastic waves resulting from localized internal micro-dis-

placements taking place in a solid. Such waves propagating

through a solid produce displacements on its surface that can

be detected by suitable transducers.

AE from metals has been studied for about 60 years

starting with the pioneering work of Kaiser [14] in 1950

to evaluate the dynamic behavior of materials. However,

serious interest in the potential of this technique for materi-

als research began only in the 1970s. AE technique has

shown an ability to explain the micromechanisms of

dynamic changes in materials and to solve problems related

to structural monitoring.

The AE technique can be used for the detection of work

hardening in austenitic stainless steels because it has the

unique potential to monitor phase transformations on-line.

AE occurs during deformation due to transient rapid

release of energy from localized sources, such as regions

of relaxation of stress and strain fields. AE generated during

deformation strongly depends on the microstructural fea-

tures, deformation processes and phase transformations

Fig. 3. Variation in BN energy (a) and hardness (b) as a function of strain [13].

Fig. 4. Variation in BN energy (a) and hardness (b) as a function of temperature [13].


[15]. AE parameters such as root mean square (r.m.s.)

voltage, ringdown counts, etc., have been used to character-

ize the deformation process of stainless steels in the past

[15,16].

AE during martensitic transformations (MTs) was

observed for the first time in 1936 by Forster and Scheil

[17], while studying a Fe–29.0% Ni steel. Acoustic signals

were recorded in the course of metallographic observations

of the specimen surface. A correlation was found between

the number of needle-type martensite crystals at the surface

and the number of acoustic signals. Since then much work in

acoustic analysis of MTs has been completed. A compre-

hensive account of this work is presented by Plotnikov and

Paskal [18]. In this paper, the possible manifestations of AE

during MTs are discussed. In the past, it was assumed that

the nature of AEs due to MT was generalized for all alloys.

Plotnikov and Paskal [18] noted that this is incorrect, and

states that acoustic activity is dependent on the material and

nature of deformation. He concludes that during forward

martensitic transformation (i.e. g ! a0), separate martensite

crystals or groups of crystals, upon their nucleation or

autocatalytic formation, are the sources of AE.

According to Ievlev et al. [19], the elementary acoustic

signal originates from the elementary acts of deformation

(dislocation slip and twinning), and its amplitude depends on

the total number of these elementary acts of deformation and

the coherency of their sources.

4.2. Acoustic analysis and work hardening

Mukhopadhyay et al. [15] used AET to characterize the

tensile deformation process in annealed and cold worked

AISI 304 stainless steel. Various techniques were used to

identify and quantify g ! a0 transformation during experi-

mentation and these results were used to corroborate the AE

results. Four cold worked conditions, 10, 20, 40, and 50%,

and one annealed stainless steels were tested (see Fig. 5). He

found that the glide distance for moving dislocations is an

important factor in acoustic activity. An intense AE is

generated in samples with low prior cold work than in

samples with high prior cold work. He concludes that this

is due to the amount of a0-martensite formation during

subsequent transformation. It is known that the formation

of a0 from g takes place through the formation of e. So, the

prior cold work first transforms the g to e thus creating the

nucleation sites for a0. The observed higher AE activity in

the 10% cold worked specimen is therefore attributed to easy

formation of a0-martensite from the e-martensite that formed

during the prior cold work. On the other hand, with increase

in prior cold work, nucleation of a0-martensite is suppressed.

The reduced emission for higher cold worked specimens

could be attributed to the decreased glide distance for

moving dislocations by prior cold work.

Jha and Baldev [20] used AE generated during tensile

plastic deformation in mild steel to give information about

Fig. 5. Engineering stress and r.m.s. voltage of AE signal versus engineering strain plots for AISI type 304 stainless steel: (a) annealed and cold worked; (b)

10%; (c) 20%; (d) 40%; (e) 50% [15].


the microscopic mechanisms (i.e. dislocation movement,

stress and strain levels) involved in deformation.

The use of AE in machining is becoming more popular of

late because it is a non-destructive sensing methodology. This

method has also been widely used in the field of metal cutting

to detect process changes like tool wear, etc. and it offers

some advantages over traditional force or power-based tool

monitoring techniques. In-process tool wear monitoring has

presently acquired more importance than ever, as manufac-

turing systems are increasingly required to provide greater

automation and flexibility, while keeping high productivity

levels. It has been found that there is a close relationship

between the generation of the emission signal and the fracture

or wear phenomenon in machining. The AE response from

metal cutting has been shown to change as the cutting tool is

worn. Several researchers using different AE techniques have

found correlations between the amount of flank or crater wear

and various AE parameters [21,22].

The major advantage of using AE to detect the condition

of tool wear is that the frequency range of the AE signal is

much higher than that of the machine vibrations and envir-

onmental noises. Therefore, a relatively uncontaminated

signal can be easily obtained by the use of a high pass filter.

In addition, AE can be measured by simply mounting a

piezoelectric transducer on the tool holder. It does not

interfere with the cutting operation thus allowing for con-

tinuous monitoring of the tool condition [21].

One of the main problems with AE as an on-line detection

technique in machining is that many different acoustic

frequencies can be emitted during a metal removal opera-

tion. Some of these are due to: tool wear, machine vibrations,

environmental noises, material removal, phase transforma-

tions within workpiece material, and different cutting para-

meters. Research into the effects of machining coolant on

AEs has not been dealt with by many researchers. The

filtering of these unwanted frequencies may be difficult if

similarities between them exist.

5. Conclusions

A review of work hardening detection techniques is

presented. Consequentially, an AE analysis technique was

chosen as the on-line detection technique that will be

employed during machining of austenitic stainless steel.

The significance of the e-martensite phase in work hard-

ening will be investigated and identified by diffraction

techniques. A micromagnetic technique will be used as a

comparator to AE results, and to quantify a0-martensite

phase transformation.

Acknowledgements

The authors gratefully acknowledge the financial assis-

tance provided for this project by Enterprise Ireland under

the Innovation Partnership Program and by MacB (Manu-

facturing) Ireland Ltd.

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Machinability of austenitic stainless steel SS303