Guideline for Multi-Criteria Decision-Making (MCDM) in Industry Energy Management: With an Application to Electric Motor Selection

The industrial sector faces one of the biggest challenges in decarbonization, mainly due to the high costs associated with the development and implementation of low-carbon, energy-efficient technologies and solutions. The long lifespan of industrial assets and infrequent replacement contribute to maintaining high levels of energy consumption and emissions. As electric motors represent a significant portion of energy consumption in industries, improving their efficiency generates substantial reductions in consumption, energy demand, and emissions, thus optimizing overall energy performance. This article proposes an integrated guideline for the application of multi-criteria decision-making (MCDM) methods, computational thinking (CT), and technical standards in industrial energy management problems. To validate this proposal, the guidelines were applied to a real-world case of electric motor selection in an industrial complex. In this context, the structured analysis of the problem, when based on computational thinking, MCDM methods, and technical standards, provides transparency and traceability to decisions. The motor-selection case study, which incorporated computational thinking and MCDM tools (AHP/TOPSIS) aligned with technical standards, demonstrated that these integrated guidelines can substantially improve decision-making in industrial contexts by structuring selection problems and aligning them with the strategic objectives of organizations.