OPTIMIZATION OF DRILLING PARAMETERS USING TAGUCHI-BASED GREY RELATIONAL ANALYSIS AND FULL FACTORIAL ANALYSIS

摘要

Metal removal process is the most prominent secondary manufacturing process in which drilling is one of the most demanding one because a completely machined geometry and surface are generated in one operation. The demands in regard to diameter precision, straightness, and surface quality are enormously high. To meet those customer demands the cutting parameters of drilling must be designed in such a way that it able to. Therefore, it is very much urgent to know about the individual effect of each process parameters and also the interaction effects of those upon the performance parameters. Otherwise, it hampers seriously customer satisfaction level. The present study focused on the influence of machining parameters on drilled hole quality obtained in drilling of AISI 1045. Cutting environment, feed rate, spindle speed, and cutting edge angle are considered as process parameters and those are designed in two levels to determine their individual and interaction effect upon surface roughness, diameter precision and taper value. Full factorial analysis, the most powerful tool of DOE is used to determine their effect. Finally, Taguchi based grey relational analysis and multiple regression analysis are adopted to provide optimum combination of process parameters considering all performance parameters and to generalize a mathematical model respectively.