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A data envelopment analysis (DEA)-based model for power interruption cost estimation for industrial companies

机译:基于工业公司的电力中断成本估算的数据包络分析(DEA)

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In this paper, a new model based on Data Envelopment Analysis (DEA) and Inverse Data Envelopment Analysis (IDEA) is presented for estimating the effect of electricity on the output of industrial companies. To this end, the effect of electricity deviation, which serves as one input that can influence a manufacturing company's final product, is evaluated. Intuitively, it is known that a direct relationship exists between electricity consumption and the output of the manufacturing company. However, finding a function that accurately represents this relationship is not easy. To check the applicability of the proposed method, it is tested on data from eight major vehicle manufacturing companies. In this model, labor hours, electrical energy consumption, and the value of raw materials are used as inputs, and the sales value is used as the proxy for the output of the company. These input and output data are used to find the efficiency of each company. Then, by changing the electricity consumption level, the output changes are derived. To calculate the outage cost, the deviation of the output is divided by the deviation of the electricity consumption, and the outage cost is estimated.
机译:本文介绍了一种基于数据包络分析(DEA)和逆数据包络分析(想法)的新模型,用于估算电力对工业公司产量的影响。为此,评估电力偏差的效果,它用于影响制造公司最终产品的一个输入。直观地,众所周知,电力消耗与制造公司的输出之间存在直接关系。但是,找到准确代表这种关系的功能并不容易。为了检查所提出的方法的适用性,它是从八个主要车辆制造公司的数据测试的。在该模型中,劳动力小时,电能消耗和原材料的价值用作输入,销售价值用作公司输出的代理。这些输入和输出数据用于找到每个公司的效率。然后,通过改变电力消耗级别,导出输出变化。为了计算中断成本,输出的偏差除以电力消耗的偏差,估计中断成本。

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