Selection of strategies to improve energy efficiency in industry: A hybrid approach using entropy weight method and fuzzy TOPSIS

Energy has now turned out to be one of the key factors for competitiveness and economic growth across the globe. In this line, the manufacturing industries have been acknowledged among the biggest drivers of economic development in all nations. Considering rapid industrial development and high rates of energy consumption, energy demand is multiplying faster than ever. Accordingly, it seems critical to improve energy efficiency (EF) and reduce energy consumption in various industries. Finding the common types of energy waste, the strategies to step up EF can consequently provide industrial owners, developers, and planners with solutions to deal with such issues. Selecting the implementation strategies for this purpose is thus assumed multi-criteria decisionmaking (MCDM) process. In the present study, the ceramic tile industry in Iran, as one of the energy-intensive industries (EIIs) due to its manufacturing process, was investigated. To this end, the strategies to improve EF and their evaluation criteria were initially established by reviewing the related literature and eliciting expert opinions. Then, the Entropy Weight Method (EWM) and the fuzzy Technique for Order Preference by Similarity to Ideal Solution (fTOPSIS) were operated to allocate weights to the criteria, and rank the given strategies, respectively. Based on the literature review, 22 EF strategies and 4 evaluation criteria were retrieved, and finally approved by the experts. The study results revealed that "cost of implementing strategies" received the highest weight among the evaluation criteria. With regard to these criteria, "Reducing leakage in the compressed air production/distribution system", Reducing power consumption of the presses, ball mills, crushers, and glazing during peak hours by shifting the load to non-peak hours", as well as "Sealing/filling the pores between the rail wall and wagon (sand seal) in tunnel kilns", were given the highest priority as the implementation strategies at factory level. Also, according to the change in the weight of the criteria, sensitivity analysis was performed for the robustness and strength of the ranking.