Introducing System Utilization Index for Energy Efficiency Evaluation and Labelling

Lakic, Edin; Gubian, Andrej; Fournely, Chloe; Djokic, Sasa

doi:10.1109/eem.2019.8916262

Cited by 1 publication

(1 citation statement)

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“…This study estimates the reduction in energy consumption on the basis of the reduction in monthly electricity consumption (MEC) brought about by the yield-learning process of a product. The novelty of this research lies in the following: in past studies, other performance measures were used for the same purpose, including production efficiency index (PEI; annual electricity consumption normalized by annual production area) and electrical utilization index (EUI; annual electricity consumption normalized by production units) [15][16][17]. Most existing indicators are annually measured.…”

Section: Introductionmentioning

confidence: 99%

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

Tsai

Chen

et al. 2021

Mathematics

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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.

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Section: Introductionmentioning

confidence: 99%