Exploration of GRA based multiobjective optimization of magnetic abrasive finishing process using simulated annealing

Magnetic abrasive finishing (MAF) process is an advanced super-finishing process that is capable of achieving surface-finish in micro to nano range. In this study a hybrid module, Taguchi based grey relational analysis (GRA) coupled with simulated annealing (SA) approach is developed for multiobjective optimization of micro-finished aluminium 6060 via MAF process. The performance responses 'change in roughness', 'raise in temperature' and 'change in hardness' are considered to minimize their impact on micro-finished aluminium 6060. These responses are used to calculate the grey relational coefficient for individual response and are then converted into a single response variable i.e. grey relational grade (GRG) value. The meta-heuristic based simulated annealing algorithm is used to predict the most desired process parameter setting i.e. working gap (2 mm), abrasive weight (15 g), voltage (6 V) and rotational speed (50 rpm). This setting has been selected based on the highest GRG value predicted by hybrid Taguchi based SA-GRA approach.