Variables Affecting the Chemical Machining of Stainless Steel 420

ISSN: 2277-3754

ISO 9001:2008 Certified

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Volume 3, Issue 6, December 2013

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Abstract— Chemical machining has a considerable value in

the solution of machining problems that are constantly arising

due to introduction of new materials and requirement for high

surface finish and dimensional accuracy, complicated shape and

special size which cannot be achieved by the conventional

machining processes. The present work is aimed at studying the

effect of machining temperature, machining time, and previous

cold working on the metal removal rate and the surface finish of

chemically machined samples of stainless steel 420 using a

mixture of acids (H

O + HCl + HNO

+ HF + HCOOH) as an

etchant. Alloy samples of (44.5×44.5×3mm) dimensions and cold

rolled alloy samples with the same dimensions were chemically

machined. Four machining temperatures (45, 50, 55, and 58

for each of which five machining times (2, 4, 6, 8, and 10min)

were used as machining conditions. The results show that

machining time, machining temperature and previous cold

working have significant effect on chemical machining products,

among these variables machining temperature has the largest

effect. Surface roughness increases with the machining

temperature and machining time, while it decreases with the

previous cold working. Metal removal rate increases with

machining temperature and decreases with previous cold

working. Stainless steel 420 rolled samples can be chemically

machined in [H2O + HCl + HNO3 + HF + HCOOH] etchants in

optimum conditions at 40ºC for 6 min, while at 40 ºC for 6 min

for the samples without cold working. An assessment of CHM

was achieved by empirical modelsfor selecting the appropriate

machining conditions for the required surface roughness and

metal removal rate. The models were designed basing on multiple

regression method via Mtb14 software.

Keywords-CHM, stainless steel, cold rolling, roughness,

metal removal, regression.

I. INTRODUCTION

The advancement of technology causes to the

development of many hard-to-machine materials due to their

high hardness, strength, brittleness, toughness and low

machining properties. Many machined components require

high surface finish and dimensional accuracy, complicated

shape and special size which cannot be achieved by the

conventional machining processes (Benedict.G.F, 1987).

Moreover, the rise in temperature and the residual stresses

generated in the work piece due to traditional machining

processes may not be acceptable. These requirements have

led to the development of non- traditional machining (NTM)

processes, one of which is the chemical machining (CHM).

This process is a precision contouring of metal into any size,

shape or form without use of physical force, by a controlled

chemical reaction. Material is removed by microscopic

electrochemical cell action, as occurs in corrosion or

chemical dissolution of a metal.

Chemical machining offers virtually unlimited scope for

engineering and design ingenuity. To gain the most from its

unique characteristics, it should be approached with the idea

that this industrial tool can do jobs not practical or possible

with any other metal working methods (Langworthy M.,

1994). It has a considerable value in the solution of

problems that are constantly arising as the result of the

introduction of new materials.

All the common metals including aluminum, copper, zinc,

steel, lead, and nickel can be chemically machined. Many

exotic metals such as titanium, molybdenum, and zirconium,

as well as nonmetallic materials including glass, ceramics,

and some plastics, can also be used with the process

(Blak.JT, DeGarmo, 2007). Chemical machining is an

effective method for the machining of shallow holes and

depressions, for profiling of the edges of sheet-metal, and

for machining of shallow cavities of large surface areas

particularly in light alloys (Drozda.T.J, 1989). CHM

applications range from large aluminum alloy airplane wing

parts to minute integrated circuit chips.

The performance of the chemical machining process is

affected by several parameters, the more important of which

are: the type of etchant solution and its concentration, the

maskant and its application, machining temperature,

machining time, and the previous cold working of the part to

be machined. Such parameters have direct effect on the

machining processes and on the characteristics of the

machined parts concerning the machining rate, production

tolerance, and surface finish. Limited efforts have been

directed towards improving the efficiency of the process.

FadaeiTehrani A. in 2004 reported that increasing of

machining temperature of stainless steel 304 causes an

increase in its machining rate and a good surface finish can

be achieved by adding triethanolamine to the etchant. David

M. Allen in 2004 showed that variations in etchant's specific

gravity, machining temperature, and oxidation–reduction

potential can affect the rate of etch with a change in etched

dimensions and surface finish. Ho S. in 2008 showed that

the rate of metal removal is up to six times greater for

nanocrystalline Ni than conventional polycrystalline Ni and

shorter working times are needed. Yao Fua in 2009 showed

that increasing the cold work level (up to 60%) steadily

decreased the corrosion resistance of the high nitrogen

stainless steel in a 3.5% NaCl solution. Kurc A. in 2010

found that Cold rolled samples shows a little lower

resistance on corrosion in artificial sea water than material

in delivery state.

There appear to need more research contribution to develop

modification of the CHM process to enhance its

performance. The present work is aimed at studying the

effect of machining temperature, machining time, and

previous cold working on the metal removal rate and the

Variables Affecting the Chemical Machining of

Stainless Steel 420

Dr. Haydar A. H. Al-Ethari, Dr. Kadhim Finteel Alsultani, Nasreen Dakhil F.

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surface finish of chemically machined alloy samples of

stainless steel 420. Each factor will take several levels in

this study. The factor's levels represent the real work

environment. Mathematical predictive models which can be

used to optimize these variables will be designed.

II. MATERIALS USED IN THE PRESENT STUDY

A. Alloy under study

A sheet (1000×1000×3 mm) of stainless steel 420 with

chemical composition shown in table (1) was used in this

work. The analyses of the chemical composition was carried

out in the State Company for Inspection and Engineering

Rehabilitation, S.I.E.R/Baghdad-Iraq.

TABLE (1) CHEMICAL COMPOSITION OF THE ALLOY UNDER STUDY

Stainles

s Steel

Alloy

Cr%

0.09

0.3

9.7

15.6

0.00

0.6

0.08

Bal

To study the effect of previous cold working, 20% cold

rolled samples had been prepared. All samples were cut to

dimensions of (44.5×44.5mm).

B. Maskant material

Depending on the used alloy, methylethylketone

peroxide was selected to prepare the maskant (El-

Hofy.H.A.-G, 2005).

C. Etchant solution

The used etchant was a mixture of acids with

concentrations demonstrated in table (2), as such chemical

composition and concentration are effective to chemically

machine the stainless steel used as a work piece

(FadaeiTehrani.A, 2004).

TABLE (2) CHEMICAL COMPOSITION AND CONCENTRATION OF THE

USED ETCHANT SOLUTION

Chemical composition

Etchant concentration (ml)

O + HCl+ HNO

+ HF +

HCOOH

1500 + 106 + 83 + 9 + 82

III. SAMPLES PREPARATION

A. Samples Preparation for CHM

Before coating with maskant material, the samples were

cleaned from dirt, dust, fats, oils and organic compounds

using alcohol (ethanol 98%). A specially designed glass

mold was used for coating the samples. After pouring the

polymeric masking material, the mold was kept in an oven

at 80 ºC for 30 min for drying. One side (face) of a sample

was left without coating, which represents the area to be

machined. A hole of 2 mm diameter was drilled in each

sample for the purpose of suspension in the etchant solution

by using plastic tongs during the machining process. Figure

(1) shows samples before and after the coating.

a. Sample before coating b. Sample after coating

FIG. (1) SAMPLES BEFORE AND AFTER COATING

The machining process was achieved via magnetic stirrer

thermostat (made in England). It contains a thermostat to

regulate the temperature of etchant during the machining

operation and controller on velocity of stirrer as shown in

Figure (2).

FIG. (2) CHEMICAL MACHINING SYSTEM

B. Samples Preparation for tests

Hardness test: Digital Display Micro Hardness Tester,

Model HVS - 1000 (China made) was used. Suitable

grinding papers (400, 800, 1000 and 2000) grit and

polishing with alumina were used to prepare the surface of

the samples. A load of 200 g with 10 seconds period for

testing was regarded. The average of three readings was

recorded.

Tafel test: Wenking M – Lab (Bank Electronik –

Intelligent controls GmbH GlessenerStrasse 60) was used in

this test to measure corrosion current, corrosion potential for

samples of (20×20mm) dimensions.

Microstructure test: Microstructure tests of the samples

were carried out by using Scanning Probe Microscope

AA3000 Scanning Probe Microscope (Angstrom Advanced

Inc, USA) that used for surface topography, microstructure

and measure surface roughness testing.

IV. CHEMICAL MACHINING PROGRAM

The alloy samples (with and without cold working) were

chemically machined according to a program included

different machining conditions. Four machining

temperatures (45, 50, 55, and 58

C) for each of which five

machining times (2, 4, 6, 8, and 10min.) were used as the

machining conditions. After each machining process, the

surface roughness, weight loss and the metal removal rate,

were recorded. The metal removal rate (MRR) was

calculated basing on the weight loss after each experiment.

The weight was measured via Sensitive weighing balance:

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ACCULAB Balance (made in china) with accuracy

±0.0001.

V. RESULTS AND DISCUSSION

A. Results of the Hardness tests

The hardness tests were carried out for the base alloy

sample and for the cold worked alloy samples before and

after the machining process. The results are demonstrated in

table (3).

TABLE (3) RESULTS OF THE VICKERS HARDNESS TESTS

Alloy sample

Vickers hardness

before CHM(g/µm

)

Vickers hardness

after CHM(g/µm

)

Without cold working

323.32

319.37

With 20% cold

working

415.96

413.74

The results indicate that the hardness of all samples does

not affected by the chemical machining process, as no

change in crystalline structure, no stresses induced by the

process, as neither mechanical deformation nor exposure to

high temperatures is involved.

B. Results of the Tafel tests

This test was used to determine the current and the

potential needed to start corrosion. All tests were carried out

with identical conditions of 40 ºC and 16 minutes duration.

Figure (3) represent the Tafel curves obtained due to this

test. The results of Tafel curves shown in table (4).

TABLE (4) RESULTS OF THE TAFEL TESTS

Alloy sample

corrosion

(mA)

corrosion

(mv)

Without cold working

0.732

-441.3

With 20% cold working

1.09

-436.8

The results indicate the following:

 The required current to start the corrosion in CHM of

alloy sample without cold working is less than that in the

deformed alloy samples. Cold working leads to increase the

value of the corrosion current density and deviation of

corrosion potential in the negative direction which is more

effective and least noble that is because of distortion in

crystals lattice of cold worked samples by plastic

deformation.

 Infer from corrosion current and potential of corrosion,

the values of machining temperature must be little greater

than the temperature at which Tafel test was carried out.

(a) With 20% cold working (b) without cold working

Fig. (3) tafel curve for the alloy sample

C. Effect of Machining Time on Ra and MRR

Figure (4) show the effect of the machining time on the

surface roughness of the machined samples at different

machining temperatures, while Figures (5) show how the

machining time affects the metal removal rate for the same

samples. The figures indicate the following:

 Increasing machining time leads to increase in surface

roughness (Ra). This can be explained on the basis of the

variety of the elements in the composition of the alloy.

Increasing the machining time leads to increase dissolving

the alloy to ions, active metal (the anode) corrodes at an

accelerated rate and the more noble metal (the cathode)

corrodes at a retarded rate and both share in the chemical

reaction with the components of the etchant as shown in

the following reactions:

Fe → Fe

-2

+2e

…………………………………..(1)

HCl → H

+ Cl

…………………………………..(2)

HNO

→ H

+ NO

……………………………...(3)

HF → H

+ F

…………………………………....(4)

+ 2e

→ H

………………………………......(5)

During metallographic etching, twin and grain boundaries

are preferentially attacked even the grain boundaries in very

high purity. Metals are slightly grooved by appropriate

etchants, the grain boundaries in impure metals and alloys

are generally much more readily etched, primarily as a result

of segregation to them the impurities and alloying additions.

Grain-boundary regions may be preferentially attacked

either because segregation makes them more active or

because segregation makes them more noble; the grain

boundary itself acts as a local cathode as stated in (Philip A.

Schweitzer, 2010).

 Cold working leads to reduce surface roughness produced

by machining for certain duration and at a certain

temperature due to distortion of the grains and their

orientation towards the rolling in sample structure.

 Decrease in metal removal rate can be noticed up to a

machining time of 6 minutes and then suddenly rises and

fall again due to increased dissolved metallic ions and its

concentrations in the etchant.

 Metal removal rates for samples without cold working are

lower than that for deformed samples for a certain

machining time and machining temperature (2and 4min.

at 45 and 50 ͦC), therefore increasing degree of cold

working leads to increase metal removal rate due to

increase in the amount of deformation, higher formation

of dislocation and their interaction with each other, which

worsen corrosion resistance.

 Increase in machining temperature leads to increase in

surface roughness. Machining temperature increases

corrosion rate as a result of high power oxidization and

mobility of ions. Also it has an effect on the etchant’s

ability to hold the dissolved metal content in solution.

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(a) 20% cold worked sample (b) base alloy sample

FIG. (4) EFFECT OF MACHINING TIME ON SURFACE ROUGHNESS FOR

THE ALLOY SAMPLES MACHINED AT DIFFERENT MACHINING

TEMPERATURES

(a)20% cold worked sample(b) base alloy sample

FIG. (5) EFFECT OF MACHINING TIME ON METAL REMOVAL RATE

FOR THE ALLOY SAMPLES MACHINED AT DIFFERENT MACHINING

TEMPERATURES

VI. OPTIMIZATION OF THE MACHINING CONDITIONS

The results of the machining experiments showed that

machining temperature, machining time and cold working

have significant and interaction effects on the roughness of

the machined surface and on the metal removal rate.

Optimum combination at these variables can be obtained by

designing mathematical models representing their relations

with the required output of the machining process –

roughness and metal removal rate.

Such models were constructed basing on the statistical

data of the carried out machining experiments. Mtb15

software was used for constructing these models basing on

the analyses of regression.

Table (5) demonstrates the constructed mathematical

models and the values of the statistical coefficients, while

Fig. (6) shows the matching between the experimental

values of surface roughness, Ra, and metal removal rate,

MRR, and their predicted values due to the designed

models. The constructed empirical models indicate the

following:

 Machining temperature has a greater effect on Ra and

MRR in comparison with the machining time and this is

independent of the cold working

 Machining for a larger duration increases the roughness of

the produced surfaces and reduces the metal removal rate,

and this is not affected by amount of cold working.

 Previous cold working reduces Ra and also MRR but at a

certain temperature for a certain time.

TABLE (5) EMPIRICAL MODELS FOR RA AND MRR

Percenta

ge of

C.W%

Empirical

model

Square

Root of

SME

Tests

to Fit

Standard

deviations

Ra = 0.0085

0.113

1.45

50.74

0.026

MRR = 10

-0.191

5.62

41.56

0.116

Ra =

0.0061

1.09

1.06

99.4

1001.8

0.023

MRR =12.8

-8

-0.261

3.2

19.65

0.105

t- Machining Time in min. ; T- Machining Temperature in

Fig (6) shows that the predicated values of the surface

roughness and the metal removal rate basing on the designed

models are close match of their experimental values.

(a) For 0% cold working

(b) For 20% cold working

FIG (6) SCATTER PLOT OF THE EXPERIMENTAL AND EMPIRICAL

VALUES OF RA AND MRR

(a) (b)

FIG. (7) RELATION BETWEEN SURFACE ROUGHNESS (RA),

MACHINING TIME AND MACHINING TEMPERATURE FOR SAMPLES:

(A) WITH 20% COLD WORKING, AND (B) WITHOUT COLD WORKING.

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(a) (b)

FIG.(8) RELATION BETWEEN METAL REMOVAL RATE, MACHINING

TIME AND MACHINING TEMPERATURE FOR SAMPLES: (A) WITH

20% COLD WORKING, AND (B) WITHOUT COLD WORKING.

Figure (9) and Fig. (10) were constructed basing on the

designed mathematical models .The figures represent the

values of the surface roughness and the metal removal rate

in the machining temperature – machining time plane.

(a) (b)

FIG.(9) MACHINING TEMPERATURE – MACHINING TIME PLANE FOR

SAMPLES WITHOUT COLD WORKING: (A)SURFACE ROUGHNESS (B)

METAL REMOVAL RATE

(a) (b)

FIG.(10) MACHINING TEMPERATURE – MACHINING TIME PLANE

FOR SAMPLES WITH 20% COLD WORKING: (A)SURFACE

ROUGHNESS (B) METAL REMOVAL RATE

Figure (11) were constructed by superimposing the values

of the surface roughness and the metal removal rate contours

in the machining temperature – machining time plane.

(a) For cold worked sample (b)For sample without cold

working

FIG. (11) SURFACE ROUGHNESS AND METAL REMOVAL RATE IN A

TEMPERATURE – TIME PLANE

Figure (11) give an ability to select an optimum combination

of machining temperature and machining time to obtain

required values for surface roughness and metal removal

rate. Finally, the results of optimum conditions for each

degree of cold working are shown in table (6).

VII. RESULTS OF TESTS BY SCANNING PROBE

MICROSCOPE

Scanning Probe Microscope was used to test samples

before and after the chemical machining. Machining

conditions were used according to the methodology

discussed and basing on Figure (11). These conditions are

demonstrated in table (6) .

TABLE (6) CHEMICAL MACHINING CONDITIONS FOR SAMPLES

TESTED BY SPM

Degree of cold

working

Temperature

ºC

time (min)

0% cold working

20% cold working

Figures (12) and Fig.(13) show microstructure, topography

and surface roughness for the tested sample by using

Scanning Probe Microscope with/without cold working

before and after chemical machining. The image size is

1994×1978 nm.

FIG. (12) SURFACE ROUGHNESS AND MICROSTRUCTURE FOR THE

SAMPLE WITHOUT COLD WORKING (A) BEFORE CHM (B) AFTER

CHM

FIG. (13) SURFACE ROUGHNESS AND MICROSTRUCTURE FOR THE

SAMPLE WITH 20% COLD WORKING (A) BEFORE CHM (B) AFTER

CHM

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The figures indicate the following:

 All grains of the deformed samples were elongated in the

direction of cold rolling. This elongation is not affected by

the chemical machining process.

 Average of measured surface roughness of the machined

samples without cold working is 2 µm, which is too close

to that can be calculated by the designed empirical model

where Ra =2.5µm and MRR=0.01 g/min. The average

surface roughness for machined samples with 20% cold

working was 1.68µm, which is also close to that can be

calculated by the designed empirical model, where Ra =

2µm and MRR=0.01 g/min. This indicates the confidence

of the designed empirical models.

 There are no metallurgical defects on the machined

surfaces due to chemical machining process.

 Microstructure is consisting of two phases (γ + M), dark

and light color, austenite phase (γ) and martensite phase

(M). After chemical machining, there is no change in

microstructure, but an increase in martesite phase (M) had

been occurred. For samples with 20% cold working the

microstructure before chemical machining contains

elongated martensite (M) within matrix of austenite phase

(γ) in crystal lattice, as the transformation of the induced

plasticity causes the grain size to be decreased.

VIII. CONCLUSIONS

Based on the detailed results the following conclusions can

be stated:

1. Machining time, machining temperature and previous

cold working are important variables that affect on

chemical machining products; among these variables

machining temperature has the largest effect.

2. Surface roughness of chemically machined parts

increases with the machining temperature and machining

time.

3. Surface roughness of chemically machined parts

decreases with the previous cold working of the work

piece.

4. Metal removal rate increases with machining

temperature and decreases with previous cold working.

5. Products of stainless steel 420 without cold working can

be chemically machined in [H

O + HCl + HNO

+ HF +

HCOOH] etchants in optimum conditions at temperature

45ºC and time 6 min.

6. Products of stainless steel 420 with 20% cold working

can be chemically machined in [H

O + HCl + HNO

HF + HCOOH] etchants in optimum conditions at

temperature 40 ºC and time 6 min.

7. An assessment of CHM can be achieved by empirical

modelsfor selecting the appropriate machining

conditions for the required surface roughness and metal

removal rate.

REFERENCES

[1] Abu Khalid Rivai, 2012, "Effect of Cold Working on The

Corrosion Resistance of JPCA Stainless Steel in Flowing"Pb–

Bi at 450◦C, Journal of Nuclear Materials 431, PP (97–104).

[2] Benedict.G.F, 1987, "Nontraditional Manufacturing

Processes", Mercel Decker Inc., New York, USA.

[3] Blak.JT, DeGarmo, 2007, "Materials and Processes in

Manufacturing", John Wiley & Sons, Inc, Tenth ed.

[4] David M. Allen, 2004, "Characterization of Aqueous Ferric

Chloride Etchant Used in Industrial Photochemical

Machining", School of Industrial and Manufacturing Science,

Cranfield University, UK.

[5] Drozda.T.J, 1989, "Tool and Manufacturing Engineers",

Handbook (Chapter 14: Nontraditional Machining), SME

Publishing.

[6] El-Hofy.H.A.-G, 2005, "Advanced Machining Processes",

Black lick, OH, USA, McGraw-Hill Companies.

[7] FadaeiTehrani.A, 2004, "A New Etchant For The Chemical

Machining of St304", Journal of Materials Processing

Technology 149, PP (404–408), Isfahan University of

Technology, Isfahan, Iran.

[8] Ho S., 2008, "Chemical Machining of Nanocrystalline Ni",

Department of Materials Science and Engineering, University

of Toronto, 184 College Street, Toronto, Canada.

[9] Kurc A. , 2010, "Influence of Cold Rolling on The Corrosion

Resistance of Austenitic Steel", Journal of Achievements in

Materials and Manufacturing Engineering, Volume 38 Issue 2.

[10] Langworthy M., 1994, "Chemical Milling By Nontraditional

machining process", Machining ASM Handbook.

[11] Philip A. Schweitzer, 2010, "Fundamentals of Corrosion,

Mechanisms", Causes and Preventative Methods, CRC Press

[12] SeropeKalpakjian, 2006, "Manufacturing, Engineering &

Technology, Fifth Edition", Pearson Education, Inc., Upper

Saddle River, NJ.

[13] SumanSamanta, 2011, "Parametric Optimization of Some

Non-traditional Machining Processes Using Artificial Bee

Colony Algorithm, Department of Production Engineering",

Jadavpur University, Kolkata, India.

[14] Yao Fu, 2009, "Effects of Cold Work and Sensitization

Treatment on The Corrosion Resistance of High Nitrogen

Stainless Steel in Chloride Solutions", ElectrochimicaActa 54,

PP (1618–1629).

AUTHOR BIOGRAPHY

Prof. Dr. Haydar A.H. Alethari

Department of Materials Engineering,

Babylon University,

Hilla-Najaf Road, P.O. 4- Al-Hilla, Iraq

E-amail: draletharihah@yahoo.com

Dr.Eng.Alethari@uobabylon.edu.iq

Haydar A.H. Alethari obtained his BSc. in Mechanical

Engineering from Mosul University-Iraq in 1981.

Then, he obtained his MS and PhD degrees from

Kharkov University (USSR-Ukraine) in 1988 and

1991, respectively. He is interested and a researcher in manufacturing,

traditional and advanced cutting processes of composites and metals.

Currently, he is a team leader of MSc. students in Materials Engineering,

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Babylon University, Iraq to develop mechanical and physical

characteristics of advanced materials.

• The number of master's students who have been supervising them (14.

• The number of the many local conferences.

• The number of international conferences in which the participant research

(14).

• Chairman of the international auditors. Arica British institution

• Dr. Kadhim F. Abdulhussein Al-sultani.

• Degree: Associate Professor.

• Marital Status – Married

• The number of children – 7.

• Bachelor of Chemical Engineering - University of

Technology - Baghdad. Materials Engineering

1990.

• Master of Chemical Engineering - University of Technology - Baghdad.

Industrial units 1999.

• PhD in Chemical Engineering - University of Technology - Baghdad.

Corrosion Engineering 2003.

• Dean of Materials Engineering College.

• Number of research published and accepted for publication more than 30

papers. Including 8 research published in international journals.

• The No. Patented – (1).