A fuzzy nonlinear programming approach for planning energy-efficient wafer fabrication factories

被引:8
|
作者
Wang, Yi-Chi [1 ]
Chiu, Min-Chi [2 ]
Chen, Toly [3 ]
机构
[1] Feng Chia Univ, Dept Ind Engn & Syst Management, Taichung, Taiwan
[2] Natl Chin Yi Univ Technol, Dept Ind Engn & Management, 57,Sec 2,Zhongshan Rd, Taichung 411, Taiwan
[3] Natl Chiao Tung Univ, Dept Ind Engn & Management, 1001 Univ Rd, Hsinchu, Taiwan
关键词
Energy efficiency; Power consumption; Yield; Fuzzy nonlinear programming; Wafer fab; ARTIFICIAL NEURAL-NETWORK; LINEAR-REGRESSION; DECISION-MAKING; YIELD; OPTIMIZATION; SIMULATION; CAPACITY; MODEL; CONSUMPTION; MANAGEMENT;
D O I
10.1016/j.asoc.2020.106506
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Wafer fabrication is an energy-consuming process. Achieving energy efficiency is, therefore, crucial for wafer fabrication factories (wafer fabs). However, limited studies have focused on resolving product quality problems for improving energy efficiency. This study proposed a novel fuzzy nonlinear programming (FNLP) approach for minimizing energy wastage caused by product quality problems. In the proposed methodology, first, the process of resolving the quality problems of a product is modeled as a fuzzy yield learning process. Then, the energy saved by the yield learning process is quantified. The total power consumption is obtained by summing the power consumptions of all the products in a wafer fab. Subsequently, an FNLP model is formulated and optimized to minimize the total energy consumption in the wafer fab by optimizing the product mix. The data from a wafer fab is used to demonstrate the applicability of the proposed FNLP approach. According to the experimental results, the total power consumption at a future period can be reduced by 17.2% by optimizing the product mix. (C) 2020 Published by Elsevier B.V.
引用
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页数:11
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