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.

中文翻译：

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采用两阶段模糊法的节能生产计划

分析能耗是工厂的一项重要任务。为了完成此任务，大多数研究都拟合了能耗与产品设计特征，过程特征或设备类型之间的关系。但是，很少考虑产品产量学习的节能效果。为了弥合这一差距，本研究提出了一种两阶段模糊方法来估算产量提高所带来的节能量。在两阶段模糊方法中，首先使用模糊多项式规划方法来拟合产品的产量学习过程。然后，拟合每月电力消耗与产量增加之间的关系，以估算产量提高所带来的节能量。使用动态随机存取存储器工厂的实际案例来说明两阶段模糊方法的适用性。根据实验结果，学习产品良率可以大大减少用电量。