Multi performance characteristics optimization in cryogenic turning of 17-4 PH stainless steel using Taguchi coupled grey relational analysis

Abstract

Cryogenic machining is one of the environmental friendly machining techniques offers high productivity in machining of difficult to cut materials. The present article investigates the multi response optimization in turning of 17-4 Precipitation Hardened Stainless Steel (PH SS) under the jetting of cryogenic coolant (liquid nitrogen) on the rake face of the cutting tool using Taguchi coupled grey relational analysis (TGRA). Cutting velocity, feed rate and depth of cut were considered as the controllable process parameters. Cutting force, surface roughness, tool flank wear and material removal rate (MRR) were considered as the performance characteristics. Experiments were performed based on Taguchi L₉ orthogonal array. From the TGRA result, it was found that at cutting velocity of 120.89 m/min, feed rate at 0.048 mm/rev and depth of cut 0.4 mm obtained the improved turning process performance characteristics. Scanning electron microscope (SEM) has been used to obtain the tool flank wear and machined surface images at the optimum machining conditions. Further analysis of variance (ANOVA) has been carried out and it was identified that feed rate was most influencing process parameter contributing 53.76% on the multi performance characteristics.

Keywords:

• Taguchi coupled grey relational analysis
• cryogenic machining
• cutting forces
• tool wear
• surface roughness
• MRR
• 17-4 PH stainless steel
• multi objective optimization

Acknowledgement

The authors are grateful to Dr. M. Pradeep Kumar, Associate professor, Department of Mechanical Engineering, Anna University, Chennai, India for providing the infrastructural facility to carry out the experimental work.