Mathematical Modeling & Multi Response Optimization for Improving Machinability of Alloy Steel Using RSM, GRA and Jaya Algorithm

Document Type : Original Article


1 Research Scholar, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Guntur, A.P, India

2 Associate Professor, Department of Mechanical Engineering, Koneru Lakshmaiah Education Foundation, Guntur, A.P, India


In order to minimise the difficulties associated in selecting conventional coolants in any machining, cutting fluids like vegetable based oils can serve as a viable alternative. Vegetable based oils when used in combination with eco-friendly techniques like MQL/NDM can have a major impact in any machining. In the present paper, performance characteristics of surface roughness and tool wear in machining of EN 36 steel alloy under Near Dry machining conditions/ Minimum quantity lubrication using vegetable based oil lubricant is studied. The input parameters like MQL flow rate, speed, feed and depth of cut for 5 levels are used in the CCD approach of Response surface methodology. For improving the machinability of alloy steel and to predit the values a regression equation is designed and developed between the input parameter and the output parameters. A multi-response optimum model for the output responses was also developed using RSM, GRA and JAYA algorithm, It was observed from the experiment results that JAYA algorithm has been proved the best multi-response optimization technique when compared to grey relational analysis and RSM.


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