Collaborative robots (COBOT) play a key role in Industry 4.0 by enabling safe human-machine interaction and flexible task execution. However, their integration adds complexity to the robot selection process, which now must consider criteria such as safety, adaptability, and collaboration, in addition to traditional technical factors. This paper presents a comprehensive review of multi-criteria decision-making (MCDM) methods and selection criteria for industrial and collaborative robots. Based on this review, a structured decision support framework is proposed, combining the PROMETHEE method to classify alternatives with the Mudge technique to assign weights to subjective criteria. The framework enables agile, transparent, and consistent robot selection without requiring a great deal of expertise in MCDM techniques. The objective is to reduce planning time, improve decision quality, and increase competitiveness in smart manufacturing environments. Future work may enhance the framework by incorporating real-world robot datasets and expanding the evaluation criteria to reflect the evolving demands of the industrial sector.
Hippert et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: