Abstract:
The Compression Resin Transfer Moulding Process (CRTM) is a popular type of Liquid Composite Moulding Process (LCM) commonly used for manufacturing composite materials. In this paper we consider the optimisation of the manufacturing processing time and the machine tooling force for the CRTM process. Since this process requires large forces during compression, force evaluation and prediction provides great advantages for the industry as it enables structural analysis of the moulds. Not only it does lead to cost effective tooling design, it also allows for proper selection of cost effective moulds and supporting equipment. The tooling force, moreover, is in conflict with manufacturing time, which is another objective of particular interest in the industry. In recent years, the advancement of CRTM simulation software allows accurate prediction of the processing objectives thus making it unnecessary to run through the expensive experiments physically. In this process, we use such a simulation software called SimLCM and combine it with a popular NSGA-II evolutionary multi-objective optimisation (EMO) algorithm to optimise maximum tooling force and processing time with respect to three manufacturing parameters. The EMO algorithm uses SimLCM as a black box to evaluate the objective function values for a population of solutions. We report results on a simple rectangular plate model (for calibration) and an industrial example.
