With the increasing demand of human–machine interaction under a scenario of the
novel Maintenance Strategy 5.0, it sparks off a growing requisition of reliable
maintenance strategies to maintain operations in good order. In this study, a
novel hierarchical maintenance strategy model based on multi-criteria decision
analysis (MCDA) is proposed to pledge scientific maintenance. First, failure
mode and effects analysis (FMEA) based on negative information and Deng entropy
is introduced to assess the equipment maintenance requirement level.
Subsequently, the improved average rank method is selected to fit the Weibull
distribution function, which is able to better qualify the characteristics
lifespan of target equipment. Moreover, hybrid effect with multi-criteria
decision-making, in aspects of risk priority, expert assessment as well as human
interference of failure are deduced, which highlights the scientific
significance and credibility of the recommended maintenance levels and times.
Finally, the feasibility of the predictive maintenance schedule is verified
through gray correlation analysis (GRA). Overall, the proposed model takes into
account the effects brought by failure modes, subjective uncertainty, and human
interference on the maintenance strategy; it, therefore, provides a new insight
on the assessment of the intertwined relationship between maintenance and
reliability.