Parameters optimization of advanced machining processes using TLBO algorithm

Nowadays advanced machining processes are widely used by manufacturing industries in order to produce high quality precise and very complex products. These advanced machining processes involve large number of input parameters which may affect the cost and quality of the products. Selection of optimum machining parameters in such advanced machining processes is very important to satisfy all the conflicting objectives of the process. In this research work a newly developed advanced algorithm is applied for the process parameter optimization of selected advanced machining processes. This algorithm is inspired by the teaching-learning process and it works on the effect of influence of a teacher on the output of learners in a class. The detailed algorithm is explained in this paper. The important advanced machining processes identified for the process parameter optimization in this work are electrochemical machining (ECM) process and electrochemical discharge machining (ECDM) process. Two different multiobjective problems of these processes are considered in this work which was attempted previously by various researchers using recent optimization technique such as artificial bee colony algorithm (ABC). However, comparison between the results gives the superiority of the new algorithm in terms of population size, number of generations and computational time.

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