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

Hsin-Chieh Wu, Horng-Ren Tsai, Tin-Chih Toly Chen and Keng-Wei Hsu
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Hsin-Chieh Wu: Department of Industrial Engineering and Management, College of Science and Engineering, Chaoyang University of Science and Technology, Taichung 413310, Taiwan
Horng-Ren Tsai: Department of Information Technology, Lingtung University, Taichung 408213, Taiwan
Tin-Chih Toly Chen: Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
Keng-Wei Hsu: Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan

Mathematics, 2021, vol. 9, issue 10, 1-17

Abstract: 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.

Keywords: electricity consumption; yield learning; fuzzy forecasting; green manufacturing (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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