کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1134892 956082 2010 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
PSO-based back-propagation artificial neural network for product and mold cost estimation of plastic injection molding
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
PSO-based back-propagation artificial neural network for product and mold cost estimation of plastic injection molding
چکیده انگلیسی

To simplify complicated traditional cost estimation flow, this study emphasizes the cost estimation approach for plastic injection products and molds. It is expected designers and R&D specialists can consider the competitiveness of product cost in the early stage of product design to reduce product development time and cost resulting from repetitive modification. Therefore, the proposed cost estimation approach combines factor analysis (FA), particle swarm optimization (PSO) and artificial neural network with two back-propagation networks, called FAPSO-TBP. In addition, another artificial neural network estimation approach with a single back-propagation network, called FAPSO-SBP, is also established. To verify the proposed FAPSO-TBP approach, comparisons with the FAPSO-SBP and general back-propagation artificial neural network (GBP) are made. The computational results show the proposed FAPSO-TBP approach is very competitive for the product and mold cost estimation problems of plastic injection molding.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 58, Issue 4, May 2010, Pages 625–637
نویسندگان
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