A human-centric approach to aid in assessing maintenance from the sustainable manufacturing perspective.

Emerging innovative manufacturing systems combine cyber-physical systems (CPS), the Internet of Things (IoT), and data analytics to develop a framework for predictive and adaptive purposes. The fifth industrial revolution, or Industry 5.0, envisions human-machine cooperation in a mutually beneficial symbiotic relationship. Human intelligence is responsible for high decision support providing feedback to the model, and the machine is dedicated to the empirical processing that builds the model. This paper presents a human-centric framework incorporating various maintenance stakeholders' perceptions to assess the relationship between key maintenance factors affecting manufacturing sustainability. The work methodology integrates two methods: the fuzzy analytic hierarchy process (F-AHP) and the elimination and choice expressing reality (ELECTRE III). The F-AHP is used to compute the relative weights of the evaluation criteria of the maintenance factors. Then, the criteria weights will be used as the input for the ELECTRE III method to rank the maintenance factors. It was observed that the proposed approach is robust and can classify the maintenance factors according to their importance to sustainable manufacturing. [ABSTRACT FROM AUTHOR]