Development of a Generic Computer Aided Deductive Algorithm for Process Parameter Design
The combined use of computer aided process simulation and design of experiment with artificial intelligence has been regarded as the most versatile way to obtain an optimal solution for the determination of a set of processing parameters at the moment. However, those proposed models are somewhat limited to particular/similar situations and mostly may not be feasible when apply to a real-life or a more complicated situation. As the number of factors/process parameters under an investigation has been increased, those suggested solutions become invalid and impractical because the complexity of work involved will increase exponentially whilst the demand of resources for setting up and maintenance of such a system is unaffordable by ordinary companies. This research study was aimed to make use the deductive approach to develop a set of guided procedures for the determination of the optimum parameter settings for a particular manufacturing process. Through the establishment of an axiom gallery, the processing parameters are sequenced and mapped systematically so that a user can just follow the workflow established. A case study that concerns with the injection moulding (IM) of a plastic toaster dust cover was included to illustrate the effectiveness of the methodology and evaluate its performance.
KeywordsDeduction Process parameter optimization Process simulation
Unable to display preview. Download preview PDF.
- 1.Turing, L.S., Peic, M.: Computer aided process and design optimization for injec-tion moulding. In: Proceedings of the institution of mechanical engineers (2002)Google Scholar
- 2.Courbebaisse, G., Garcia, D.: Shape analysis and injection molding optimization. Computational materials science (2002)Google Scholar
- 3.Sadeghi, B.H.M.: A BP-neural network predictor model for plastic injection molding process. Journal of materials processing technology (2000); Yarlagadda, P.K.D.V.: Development of an integrated neural network system for prediction of process parameters in metal injection moulding. Journal of materials processing technology (2002)Google Scholar