2Application of Flower Pollination Algorithm for Optimization of ECM Process Parameters

The flower pollination algorithm (FPA), a novel metaheuristic algorithm inspired by the natural pollination of flowers, is employed for optimization of the electrochemical machining (ECM) process. The objective function used in the FPA for optimization is developed using response surface methodology (RSM). RSM is used to develop empirical equations in order to map the inter-relationship between ECM process parameters (electrolyte flow rate, electrolyte concentration, feed rate, voltage and inter-electrode gap) and response variables. Optimal results are predicted by using the FPA to satisfy single-criteria as well as multiple-criteria optimization. The performance of the FPA is evaluated by accuracy of the results, convergence speed, the number of optimized populations and computational time. The FPA is also used to draw the trend lines of responses corresponding to different ECM parameters. The results of the present research work are compared to those presented by past studies to validate the superiority of the FPA in terms of accuracy and effectiveness.

2.1. Introduction

Electrochemical machining (ECM) stands out among the most potential modern machining technologies. It uses the principle of electrolysis to remove the metal from a workpiece. If two electrodes are placed in a liquid bath filled with conductive fluid and a DC potential is applied between the electrodes, and then the ...

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