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Optimizing the Performance of Plastic Injection Molding Using Weighted Additive Model in Goal Programming

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  • Abbas Al-Refaie

    (University of Jordan, Jordan)

  • Ming-Hsien Li

    (Feng Chia University, Taiwan)

Abstract

Injection molding process is increasingly more significant in today’s plastic production industries because it provides high-quality product, short product cycles, and light weight. This research optimizes the performance of this process with three main quality responses: defect count, cycle time, and spoon weight, using the weighted additive goal programming model. The three quality responses and process factors are described by appropriate membership functions. The Taguchi’s orthogonal array is then utilized to provide experimental layout. A linear optimization based on the weighted additive model in goal programming model is built to minimize the deviations of the product/process targets from their corresponding imprecise fuzzy values specified by the process engineer’s preferences. The results show that the average defect count is reduced from an average of 0.75 to 0.16. Moreover, the average cycle time becomes 13.06 seconds, which is significantly smaller than that obtained at initial factor settings (= 15.10 seconds). Finally, the average spoon weight is exactly on its target value of 2.0 gm.

Suggested Citation

  • Abbas Al-Refaie & Ming-Hsien Li, 2011. "Optimizing the Performance of Plastic Injection Molding Using Weighted Additive Model in Goal Programming," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 1(2), pages 43-54, April.
    • Handle: RePEc:igg:jfsa00:v:1:y:2011:i:2:p:43-54
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    Cited by:

    1. Abbas Al-Refaie & Wafa’a Al-Alaween & Ali Diabat & Ming-Hsien Li, 2017. "Solving dynamic systems with multi-responses by integrating desirability function and data envelopment analysis," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 387-403, February.

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