A Data Envelopment Analysis (DEA)-Based Model for Power Interruption Cost Estimation for Industrial Companies

TL;DR

This paper introduces a DEA-based model to estimate power interruption costs for industrial firms by analyzing how electricity deviations impact output, tested on vehicle manufacturers.

Contribution

It presents a novel DEA and IDEA-based approach to quantify the effect of electricity deviations on industrial output and outage costs.

Findings

Model effectively estimates outage costs based on electricity deviation impacts.

Applied successfully to data from eight vehicle manufacturing companies.

Provides a practical method for power interruption cost assessment.

Abstract

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.