| Summary: | 碩士 === 中華大學 === 科技管理研究所 === 94 === In this research, design of experiment (DOE) method is employed to analyze the more eminent and crucial process parameters of control factors with respect to the weight of product in injection molding system (IMS) and further locate their dependences. The effect of multi-variables vs. system performance and the interacted impact benefits among process parameters are assessed by the various sets of injection velocity, injection pressure, injection time and material temperature. In addition, the study identifies the initial optimal operational variables via IMS experiments to develop the process model using design of experiment method, and adopts the recursive least squares (RLS) algorithm to create on-line adjustments of process model which can control the process shifts and drifts. Moreover, the adjusted model enables the output variables promptly to reach our setting target and increase the product quality as applying the minimum variance controller (MVC). Finally, the research represents the response surface model to generate the precise process model through the injection velocity, injection pressure, injection time and material temperature, and exploits the above process model to conduct the process control and raise the quality of product.
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