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

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 r...

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Bibliographic Details
Published in:Mathematics (Basel) 2021-05, Vol.9 (10), p.1101
Main Authors: Wu, Hsin-Chieh, Tsai, Horng-Ren, Chen, Tin-Chih Toly, Hsu, Keng-Wei
Format: Article
Language:English
Subjects:
Approximation
Dynamic random access memory
Electric rates
Electricity
Electricity consumption
Energy consumption
Factories
fuzzy forecasting
Fuzzy sets
green manufacturing
Learning
Literature reviews
Manufacturing
Mathematical functions
Mathematics
Methods
Point defects
Polynomials
Product design
Production planning
yield learning
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Summary: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.
ISSN:2227-7390
2227-7390
DOI:10.3390/math9101101