Evolutionary modelling and optimization of grinding processes

The objective of this study is to develop a framework of modelling the comp lex grinding processes and finding optimal process conditions to meet the g eneral class of process requirements. In order to achieve the above goal, n ovel modelling schemes and optimization methods based on evolutionary algor ithms (EA) are developed. The optimization problem of grinding processes ca n be formulated as a constrained non-linear programming problem with mixed- discrete variables. The adaptive least-squares (ALS) algorithm proposed by Lee and Shin's 1998 study is extended for modelling multi-input-multi-outpu t (MIMO) complex grinding processes using fuzzy basis function networks (FB FN), while the modified evolution strategies (ES) is proposed for successfu l optimization of grinding processes. Two grinding optimization problems de monstrate the superior performance of the proposed scheme.