Particle swarm optimization for optimal process parameters in injection molding

Abstract

Injection molding is a manufacturing process where the products or parts are made from plastic, glasses or other materials. In simple word, this process is involved with melting the required materials and injected it into the mold to produce a product or part. One of the biggest problems in manufacturing is to minimize the cost of producing a product without affecting their final product quality. To produce a high quality product using injection molding process, it is important to control efficiently the parameters involved in this manufacturing process. When one of these parameters has not been controlled efficiently, the quality of the final product can be affected. Soft computing technique can offer an option to evaluate this process efficiently at low cost before being applied by factory in creating and producing high quality product. This study focused on finding the optimal parameters’ combination to produce high quality product using Particle Swarm Optimization (PSO). Based on the previous researches, PSO have been known as reliable soft computing techniques in optimization problems. The results found that PSO improved the minimum warpage value by 1.2111% compared to observed data.