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Multi-response optimization in environment friendly turning of AISI 304 austenitic stainless steel

Purpose The purpose of this paper is to investigate the influence of turning parameters such as cutting speed, feed rate and depth of cut on tool flank wear and machined surface quality of AISI 304 stainless steel during environment friendly turning under nanofluid minimum quantity lubrication (NMQL...

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Published in:Multidiscipline modeling in materials and structures 2019-05, Vol.15 (3), p.538-558
Main Authors: Singh, Talwinder, Dureja, J.S, Dogra, Manu, Bhatti, Manpreet S
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description Purpose The purpose of this paper is to investigate the influence of turning parameters such as cutting speed, feed rate and depth of cut on tool flank wear and machined surface quality of AISI 304 stainless steel during environment friendly turning under nanofluid minimum quantity lubrication (NMQL) conditions using PVD-coated carbide cutting inserts. Design/methodology/approach Turning experiments are conducted as per the central composite rotatable design under the response surface methodology. ANOVA and regression analysis are employed to examine significant cutting parameters and develop mathematical models for VB (tool flank wear) and Ra (surface roughness). Multi-response desirability optimization approach is used to investigate optimum turning parameters for simultaneously minimizing VB and Ra. Findings Optimal input turning parameters are observed as follows: cutting speed: 168.06 m/min., feed rate: 0.06 mm/rev. and depth of cut: 0.25 mm with predicted optimal output response factors: VB: 106.864 µm and Ra: 0.571 µm at the 0.753 desirability level. ANOVA test reveals depth of cut and cutting speed-feed rate interaction as statistically significant factors influencing tool flank wear, whereas cutting speed is a dominating factor affecting surface roughness. Confirmation tests show 5.70 and 3.71 percent error between predicted and experimental examined values of VB and Ra, respectively. Research limitations/implications AISI 304 is a highly consumed grade of stainless steel in aerospace components, chemical equipment, nuclear industry, pressure vessels, food processing equipment, paper industry, etc. However, AISI 304 stainless steel is considered as a difficult-to-cut material because of its high strength, rapid work hardening and low heat conductivity. This leads to lesser tool life and poor surface finish. Consequently, the optimization of machining parameters is necessary to minimize tool wear and surface roughness. The results obtained in this research can be used as turning database for the above-mentioned industries for attaining a better machined surface quality and tool performance under environment friendly machining conditions. Practical implications Turning of AISI 304 stainless steel under NMQL conditions results in environment friendly machining process by maintaining a dry, healthy, clean and pollution free working area. Originality/value Machining of AISI 304 stainless steel under vegetable oil-based NMQL conditions has not been inve
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Design/methodology/approach Turning experiments are conducted as per the central composite rotatable design under the response surface methodology. ANOVA and regression analysis are employed to examine significant cutting parameters and develop mathematical models for VB (tool flank wear) and Ra (surface roughness). Multi-response desirability optimization approach is used to investigate optimum turning parameters for simultaneously minimizing VB and Ra. Findings Optimal input turning parameters are observed as follows: cutting speed: 168.06 m/min., feed rate: 0.06 mm/rev. and depth of cut: 0.25 mm with predicted optimal output response factors: VB: 106.864 µm and Ra: 0.571 µm at the 0.753 desirability level. ANOVA test reveals depth of cut and cutting speed-feed rate interaction as statistically significant factors influencing tool flank wear, whereas cutting speed is a dominating factor affecting surface roughness. Confirmation tests show 5.70 and 3.71 percent error between predicted and experimental examined values of VB and Ra, respectively. Research limitations/implications AISI 304 is a highly consumed grade of stainless steel in aerospace components, chemical equipment, nuclear industry, pressure vessels, food processing equipment, paper industry, etc. However, AISI 304 stainless steel is considered as a difficult-to-cut material because of its high strength, rapid work hardening and low heat conductivity. This leads to lesser tool life and poor surface finish. Consequently, the optimization of machining parameters is necessary to minimize tool wear and surface roughness. The results obtained in this research can be used as turning database for the above-mentioned industries for attaining a better machined surface quality and tool performance under environment friendly machining conditions. Practical implications Turning of AISI 304 stainless steel under NMQL conditions results in environment friendly machining process by maintaining a dry, healthy, clean and pollution free working area. 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Confirmation tests show 5.70 and 3.71 percent error between predicted and experimental examined values of VB and Ra, respectively. Research limitations/implications AISI 304 is a highly consumed grade of stainless steel in aerospace components, chemical equipment, nuclear industry, pressure vessels, food processing equipment, paper industry, etc. However, AISI 304 stainless steel is considered as a difficult-to-cut material because of its high strength, rapid work hardening and low heat conductivity. This leads to lesser tool life and poor surface finish. Consequently, the optimization of machining parameters is necessary to minimize tool wear and surface roughness. The results obtained in this research can be used as turning database for the above-mentioned industries for attaining a better machined surface quality and tool performance under environment friendly machining conditions. 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Design/methodology/approach Turning experiments are conducted as per the central composite rotatable design under the response surface methodology. ANOVA and regression analysis are employed to examine significant cutting parameters and develop mathematical models for VB (tool flank wear) and Ra (surface roughness). Multi-response desirability optimization approach is used to investigate optimum turning parameters for simultaneously minimizing VB and Ra. Findings Optimal input turning parameters are observed as follows: cutting speed: 168.06 m/min., feed rate: 0.06 mm/rev. and depth of cut: 0.25 mm with predicted optimal output response factors: VB: 106.864 µm and Ra: 0.571 µm at the 0.753 desirability level. ANOVA test reveals depth of cut and cutting speed-feed rate interaction as statistically significant factors influencing tool flank wear, whereas cutting speed is a dominating factor affecting surface roughness. Confirmation tests show 5.70 and 3.71 percent error between predicted and experimental examined values of VB and Ra, respectively. Research limitations/implications AISI 304 is a highly consumed grade of stainless steel in aerospace components, chemical equipment, nuclear industry, pressure vessels, food processing equipment, paper industry, etc. However, AISI 304 stainless steel is considered as a difficult-to-cut material because of its high strength, rapid work hardening and low heat conductivity. This leads to lesser tool life and poor surface finish. Consequently, the optimization of machining parameters is necessary to minimize tool wear and surface roughness. The results obtained in this research can be used as turning database for the above-mentioned industries for attaining a better machined surface quality and tool performance under environment friendly machining conditions. Practical implications Turning of AISI 304 stainless steel under NMQL conditions results in environment friendly machining process by maintaining a dry, healthy, clean and pollution free working area. Originality/value Machining of AISI 304 stainless steel under vegetable oil-based NMQL conditions has not been investigated previously.</abstract><cop>Bingley</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/MMMS-07-2018-0139</doi><tpages>21</tpages></addata></record>
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subjects Aircraft components
Austenitic stainless steels
Cutting parameters
Cutting speed
Cutting wear
Feed rate
Floods
Fluids
Food industry
Food processing
Food processing industry
Heat conductivity
Inserts
Lubrication
Mathematical models
Nanofluids
Nanoparticles
Nuclear reactor components
Optimization
Organic chemistry
Pressure vessels
Production planning
Regression analysis
Response surface methodology
Stainless steel
Statistical analysis
Steel alloys
Surface finish
Surface properties
Surface roughness
Thermal conductivity
Titanium alloys
Tool wear
Work hardening
title Multi-response optimization in environment friendly turning of AISI 304 austenitic stainless steel
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