An experimental investigation to optimise injection moulding process parameters for plastic parts by using Taguchi method and multi-objective genetic algorithm

Deepak Kumar, G.S. Dangayach and P.N. Rao

International Journal of Process Management and Benchmarking, 2019, vol. 9, issue 1, 1-26

Abstract: Plastic injection moulding is a useful method to produce plastic parts with high-quality surface finish. Improper process parameter settings can cause many production troubles namely defective products, reduce dimensional precision and scrap. Thus, determining the optimal processing parameters is regularly performed in injection moulding industry. In this paper, to determine the initial range of process parameters steady state experiments were performed. Taguchi method and multi objective genetic algorithm are used to optimise the process parameters of electric meter box and to reduce its shrinkage and warpage and to enhance its impact strength. For this purpose L₂₇ orthogonal array was used. The modified linear graph was used with the line separation method to assign the parameters and interactions to various columns of the orthogonal array. The confirmation experiments show that the errors associated with prediction of shrinkage, warpage and impact strength are 5.11%, 5.91% and 1.171% respectively.

Keywords: injection moulding; process parameters; Taguchi method; multi-objective genetic algorithm; steady state experiments; modified linear graph; prediction; shrinkage; warpage and impact strength. (search for similar items in EconPapers)
Date: 2019
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