A fuzzy ANP-based criticality analyses approach of reliability-centered maintenance for CNC lathe machine components

Calculation of the criticality score and its analysis are important for the reliability-centered maintenance (RCM) of CNC lathe machine components. The tools of a CNC lathe machine include complex critical part and sub-systems. The reliability of parts decline due to the independent system fault. To identify the essential components of CNC lathe machine tools, a system level component criticality analysis method is proposed. In this study, a comprehensive framework of criticality-based RCM implementation through experimentation of a CNC-lathe machine is proposed. The criticality of machine components were identified by investigating their dependency on the criteria and sub-criteria. Five main criteria were found effective for the criticality of the components which are the cost, complexity, sustainability, functional dependency, and safety impacts. Fuzzy analytical network process (FANP) approach was employed to evaluate criticality scores for eleven-component of a CNC lathe machine. This is a preliminary study and aims to contribute to the literature and practitioners in many ways. The primary focus of our method lies in its capability to predict criticality values for a manufacturing system in absence of historical maintenance data relying on the expertise/intuition of the operator(s) for decision making for the predictive maintenance of the system with the help of fuzzy ANP approach. It was found that the turret was the most critical component with a metric of 0.0641 which was also found to be over 3 times more critical than the least critical hydraulic system, which had a criticality metric of 0.0187. This novel FANP framework provides a credible solution to real-world RCM scheduling and can be applied to any manufacturing system-related application.