Analysis of Maintenance 5.0 Implementation Challenges: An Interpretive Structural Modeling (ISM) and Fuzzy MICMAC

This paper aims to identify and analyze the maintenance 5.0 implementation challenges in the manufacturing industry. This study applied an approach by developing a structural relationship model based on interpretive structural modeling (ISM) and fuzzy input-based cross-impact matrix multiplication applied to classification (MICMAC) to analyze and prioritize the challenges impacting the implementation of maintenance 5.0 approaches. Results confirmed that the barriers, complexity of technology (CT), and cybersecurity risks (CSR) are situated at the lowest level of the hierarchy, alluding to an important driver power. The barriers of insufficient and poor-quality data (IPD), lack of adequate training (LAT), and lack of qualified workforce (LQW) are identified in the category of the linkage challenges with strong driving and dependence powers. It is also observed that the high implementation costs (HIC) is a feeble driver but heavily dependent on the other challenges. The findings of this study simplify the process for decision-makers to address and mitigate these barriers. Further, the limitations of this study have been listed, offering opportunities for further investigation in this research area. Finally, future research directions and theoretical and managerial implications are discussed.