Multi-Response Optimization of Compression Molding Process to Increase Flexural Strength and Reduce Electrical Conductivity of GF/PP

This study focuses on exploring how compression molding parameters influence the properties of conducting polymer composites (CPC), specifically their electrical conductivity and flexural strength. Graphite (G) is used as the filler, and polypropylene (PP) serves as the binder in the CPC formulation. In this study, the response surface methodology is utilized to create the experimental design. A set of 27 experiments were conducted as per DOE. The range of pressure 60–120 kgf/cm2, temperature 150–300, curing time 20–40 s is selected as process control parameters. The electrical conductivity and flexural strength are considered as process outcome. The electrical conductivity is measured and the flexural strength is measured. This research data is used to develop a regression model for the two responses. For data analysis, analysis of variance (ANOVA) is applied to evaluate the significance of compression molding parameters on the electrical conductivity and flexural strength of the CPC. The process is optimized using the Rao-1 algorithm. Subsequently, the optimum compression molding parameters are proposed based on the findings.