Parametric Appraisal of Plastic Injection Moulding for Low Density Polyethylene (LDPE): A Novel Taguchi Based Honey Badger Algorithm and Capuchin Search Algorithm

In our quickly growing world, there is an increasing need for cheap, long-lasting, and less hazardous materials for medical purposes. To meet their needs, medical goods ranging from intravenous fluid containers to medical syringes are manufactured utilizing a variety of thermoplastics and Plastic Injection Moulding (PIM). Even sophisticated profile mouldings, however, may suffer from dimensional inaccuracy. The present research contributes to a better knowledge of thermoplastics, namely Low-Density Polyethylene (LDPE) material moulding for medical syringe plungers utilizing injection moulding equipment. Eight input injection moulding parameters were examined to reduce the depth sink marks along with weight produced during injection moulding of thermoplastic LDPE material. The 27 trials were piloted in accord with Taguchi's Design of Experiment, and the variables were optimized using the newly developed Honey Badger and Capuchin Search Algorithms, as well as analysis of variance, for determining the most dominating parameter. The cooling time and melt temperature of the plastic injection moulded part are the most significant factors influencing the sink-mark depth and weight of the part respectively, according to the Analysis of Variance (ANOVA) test.