The cooling process is of great importance in plastic injection moulding as it has a direct impact on both productivity and product quality. Cooling process optimization is a sophisticated task which includes not only the design of cooling channels but also the selection of process parameters. Most existing optimization systems focus on either cooling channel design or process parameter selection but not both. This paper explores an approach to optimize both cooling channel design and process condition selection simultaneously through an evolutionary algorithm. The prototype system proposed in this paper is an integration of the genetic algorithm and CAE (Computer-Aided Engineering) technology. The aim is to launch a computerized system that can guide the optimization of the cooling process in plastic injection moulding. The objective is to achieve the most uniform cavity surface temperature to assure product quality.
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Management Science and Operations Research