An Experimental Investigation To Optimise Injection Moulding Process Parameters For Plastic Parts By Using Taguchi Method And Multi-Objective Genetic Algorithm
Impact strength, Injection moulding, Modified linear graph, Multi-objective genetic algorithm, Prediction, Process parameters, Shrinkage, Steady state experiments, Taguchi method, Warpage
International Journal of Process Management and Benchmarking
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.
Department of Technology
Original Publication Date
DOI of published version
UNI ScholarWorks, Rod Library, University of Northern Iowa
Kumar, Deepak; Dangayach, G. S.; and Rao, P. N., "An Experimental Investigation To Optimise Injection Moulding Process Parameters For Plastic Parts By Using Taguchi Method And Multi-Objective Genetic Algorithm" (2019). Faculty Publications. 611.