Chemical Engineering |
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Multi-objective process parameter optimization for energy saving in injection molding process |
Ning-yun Lu, Gui-xia Gong, Yi Yang, Jian-hua Lu |
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; Department of Control Engineering and Science, Zhejiang University, Hangzhou 310027, China; School of Computer Science and Engineering, Southeast University, Nanjing 210096, China |
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Abstract This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process. It combines an experimental design by Taguchi’s method, a process analysis by analysis of variance (ANOVA), a process modeling algorithm by artificial neural network (ANN), and a multi-objective parameter optimization algorithm by genetic algorithm (GA)-based lexicographic method. Local and global Pareto analyses show the trade-off between product quality and energy consumption. The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests, and at the same time, the product quality can meet the pre-determined requirements.
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Received: 02 November 2011
Published: 04 May 2012
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