Enhancing smart energy load management in industrial steel production using the fermatean fuzzy FUCA multi-criteria analysis

The bottom line in industrial steel manufacturing is effective energy load management to lower the cost and increase sustainability. This paper develops a new decision-making model based on the Fermatean Fuzzy FUCA (FF-FUCA) approach for prioritizing innovative energy load strategies in the face of uncertainty. There were fifteen options considered under various benefit and cost parameters, along with professional opinion. The findings show that the suggested strategy helps determine the most effective and feasible strategies, and deselects the alternatives that are more expensive or less feasible. Sensitivity analysis was used to ensure the rankings remain stable in the face of changes in decision-makers' weights and criteria weights. Benchmarking against existing FF multi-criteria decision-making (MCDM) methods showed the high reliability and balance of FF-FUCA. The study is practical in advising managers in the steel industry on selecting cost-effective, sustainable energy solutions, as well as augmenting fuzzy MCDM by demonstrating the improved performance of FF-FUCA in decision-making processes within complex industrial settings.