Multi-Objective Optimization of Particle Reinforced Silicone Rubber Mould Material for Soft Tooling Process

Multi-objective optimizations of various conflicting objectives in designing particle reinforced silicone rubber are conducted using evolutionary algorithms to reduce the processing time of soft tooling process. A well-established evolutionary algorithm based multi-objective optimization tool, NSGA-II is adopted to find the optimal values of design parameters. From the obtained Pareto-optimal fronts, suitable multi-criterion decision making techniques are used to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of soft tooling process for industrial applications.