Abstract
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.
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Cheng, K.P., Yip, D.C.Y., Lau, K.H., Barnes, S. (2004). Development of a Generic Computer Aided Deductive Algorithm for Process Parameter Design. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_4
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DOI: https://doi.org/10.1007/978-3-540-30133-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23206-3
Online ISBN: 978-3-540-30133-2
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