Response Surface Modeling and Grey Relational Analysis to Optimize Turning Parameters with Multiple Performance Characteristics

Abstract

Optimization of process parameters is the key step in response surface methods to achieve high quality without cost inflation. The multi-response optimization of the machining parameters viz, chip-tool interface temperature, main cutting force and feed force on lathe turning of En-31 steel as alloy steel using RSM with grey relational analysis is reported. A grey relational grade obtained from the grey relational analysis is used to solve the turning operations with multiple performance characteristics. The models were developed using response surface methodology. Optimal cutting parameters can be determined by RSM method using the grey relational grade as the performance index. Chip-tool interface temperature, main cutting force, and feed force are important characteristics in turning operations. Using these characteristics, the cutting operations, including cutting velocity, feed rate, depth of cut, and effective tool nose radius, are optimized. A model is developed to correlate the multiple performance characteristic called grey relational grade and turning parameters and a new combination of RSM and grey relational analysis is proposed. The grey relational grades were significantly affected by cutting parameters and tool nose radius. Optimal parameter setting is determined for the multi-performance characteristic.