Intelligent model-based optimization of the surface grinding process for heat-treated 4140 steel alloys with aluminum oxide grinding wheels

This paper presents implementation results of surface grinding processes based on the model-based optimization scheme proposed by Lee and Shin (Lee, C. W., and Shin, Y C., 2000 "Evolutionary Modeling and Optimization of Grinding Processes," Int. J. Prod. Res. 38(12), pp. 2787-2813). In order to accomplish this goal, process models for grinding force, power surface roughness, and residual stress are developed based on the generalized grinding model structures using experimental data. The time-varying characteristics due to wheel wear are also investigated in order to determine the optimal dressing interval. Grinding optimization is considered as constrained nonlinear optimization problems with mixed-integer variables and time-varying characteristics in this study. Case studies are performed with various optimization objectives including minimization of grinding cost, minimization of cycle time, and process control. The optimal process conditions determined by the optimization scheme are validated by experimental results.