Computational model for predicting the effect of process parameters on surface characteristics of mass finished components. Issue 3 (3rd May 2016) - Vijayaraghavan, Venkatesh; Castagne, Sylvie
Abstract : Purpose: – Mass finishing is a commonly employed surface finishing process for improving surface characteristics of aerospace engineering components. Optimization of surface characteristics of such critical components require an explicit computational model that can describe the surface characteristics of the finished component. The purpose of this paper is to develop an explicit computational model that can describe the surface roughness as a function of various process parameters which influence the mass finishing process. Design/methodology/approach: – In the present work, the authors propose to study the roughness characteristics using a combined evolutionary computing approach based on Multi-Adaptive Regression Splines and Genetic Programming (GP) techniques. Findings: – The authors conducted sensitivity and parametric analysis to capture the dynamics of surface characteristics by unveiling dominant input variables and hidden non-linear relationships. It is found that by regulating the process time and media size, a greatest variation in surface finish reduction can be achieved in mass finishing process. Originality/value: – To the best of authors knowledge, for the first time a hybrid evolutionary computational technique has been proposed in this work. The authors combined two powerful evolutionary techniques, namely Multi-variate Adaptive Regressive Splines and GP approach. The proposed approach was able to capture the dynamics of surface roughness with higher accuracy as comparable to that of the experiments.