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

• Main Authors: Hsin-Chieh Wu, Horng-Ren Tsai, Tin-Chih Toly Chen, Keng-Wei Hsu
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Mathematics
• Subjects: electricity consumption; yield learning; fuzzy forecasting; green manufacturing
• Online Access: https://www.mdpi.com/2227-7390/9/10/1101

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.