No abstract

No abstract

The multi-stage sequential process with multi-objective is a complex problem to address as the decision made at a particular stage influences the subsequent stage and vice versa. In this article, the effects of input variables of plastic injection, mold, and different plating stages were investigated on different output responses, namely weldline, warpage, length, and various metal plating thicknesses. This paper investigates a real-time industrial data of manufacturing an automotive exterior part made of ABS material. A D-optimal experimental layout with 55 experiments was generated for eight input factors each at three levels. Nine different output responses in each experiment were normalized into a weighted grey relational grade using grey relational analysis coupled with principal component analysis. The solutions obtained by the analysis of variance on weighted grey relational grade, and by the desirability analysis of D-optimal were compared and validated. The confirmation experiments recorded an average improvement in cumulative process outputs as 40.56% by grey relational analysis and 38.50% by desirability analysis.

This work is done in order to get the optimized process setting for an ABS Molded part which is molded in ABS, LG MP 220 Grade materials for an automotive requirement which is plated. The specimen sample is made in injection molding machine and we have used Response Surface Methodology, We have tried to optimize the process by picking 4 important process parameter which are variable in the molding machine which are Injection Time(IT),Holding Time(HT),Refilling time and the Mold closing Time(MCT) and these are taken to get an output which is Cycle time and it has been evaluated through an ANOVA table to understand the effect of Cycle time based on varying the parameters which gives us an ideal setting of the parameters for an Ideal cycle time based on the experiments.

No abstract