Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach

被引:2
|
作者
Wu, Hsin-Chieh [1 ]
Tsai, Horng-Ren [2 ]
Chen, Tin-Chih Toly [3 ]
Hsu, Keng-Wei [3 ]
机构
[1] Chaoyang Univ Sci & Technol, Coll Sci & Engn, Dept Ind Engn & Management, Taichung 413310, Taiwan
[2] Lingtung Univ, Dept Informat Technol, Taichung 408213, Taiwan
[3] Natl Yang Ming Chiao Tung Univ, Dept Ind Engn & Management, Hsinchu 30010, Taiwan
关键词
electricity consumption; yield learning; fuzzy forecasting; green manufacturing; COLLABORATIVE INTELLIGENCE APPROACH; WAFER FABRICATION; SCHEDULING PROBLEM; PRODUCTION SYSTEM; OPTIMIZATION; YIELD; TIME; SUSTAINABILITY; COMPETITIVENESS; CONSUMPTION;
D O I
10.3390/math9101101
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Analyzing energy consumption is an important task for a factory. In order to accomplish this task, most studies fit the relationship between energy consumption and product design features, process characteristics, or equipment types. However, the energy-saving effects of product yield learning are rarely considered. To bridge this gap, this study proposes a two-stage fuzzy approach to estimate the energy savings brought about by yield improvement. In the two-stage fuzzy approach, a fuzzy polynomial programming approach is first utilized to fit the yield-learning process of a product. Then, the relationship between monthly electricity consumption and increase in yield was fit to estimate the energy savings brought about by the improvement in yield. The actual case of a dynamic random-access memory factory was used to illustrate the applicability of the two-stage fuzzy approach. According to the experiment results, product yield learning can greatly reduce electricity consumption.
引用
收藏
页数:17
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