A grey relational analysis is a novel technique for forecast, developing relational analysis and in decision-making in numerous areas of manufacturing or production processes in industry. In this investigation, an attempt has been made to optimize input process parameters considering assigned weight fraction of output quality characteristics using grey relational analysis. The output quality characteristics considered are thrust force, torque and surface roughness under the experimental domain of cutting speed, feed, step diameter and point angle. The drilling experiments were designed as per Taguchi design of experiments using L 9 orthogonal array. The combined methodology of orthogonal array design of experiments and grey relational analysis was implemented to establish the best possible input process parameters that give minimum thrust force, torque and surface roughness. The results reveal that with the help of grey relational analysis, output quality characteristics can be enhanced efficiently.
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Singh et al. (2013) studied this question.
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