Reducing energy consumption in industrial plants: An Integrated Multi- Criteria Decision-Making Framework with Similarity Aggregation Method

The reduction of energy consumption in manufacturing industries has become a primary focus, driven by increased environmental awareness and the introduction of European Directives. Adopting energy-saving solutions can not only reduce environmental impact but also enhance production performance. A prevalent strategy for achieving higher energy efficiency involves the replacement of outdated technologies within production plants. This approach is widely adopted across various industrial sectors; however, selecting the most appropriate technology is a complex task due to the vast array of solutions available in the market. Multi-Criteria Decision-Making (MCDM) methods can be employed to address this challenge, but the choice of a suitable MCDM tool is crucial, as different tools may yield varying results. Additionally, MCDM approaches typically necessitate expert elicitation, which often entails integration with Fuzzy Set Theory (FST) to manage subjectivity and uncertainty arising from expert judgments. It is essential to appropriately aggregate differing expert opinions, considering both the importance of each expert and the consensus among them. This paper proposes an integrated MCDM framework that combines a robust approach for aggregating expert opinions. We achieve this by combining the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods, offering increased flexibility for users. Simultaneously, the improved Similarity Aggregation Method (SAM) is employed to aggregate the opinions of various experts, taking into account the degree of consensus. The developed framework is demonstrated through a case study of a cement plant, and it can be utilized to identify the most suitable technology for a given enterprise.