Failure mode identification and effects analysis of mobile X-ray machine using selected MADM techniques - Vikas Sisodia; Dharmalingam Ganesan; Sachin Salunkhe; Robert Čep; Emad Abouel Nasr (Scientific Reports)
Abstract Failure mode and effects analysis (FMEA) is a method of reliability analysis that healthcare organizations employ to increase the reliability and safety of their services and products. In the healthcare devices & equipment segment, X-ray devices hold a special place among them. Nowadays, global healthcare device brands are focusing on mobile units for X-ray devices due to their advantage of mobility, and one of the significant challenges is the failure to address issues with the mobility of mobile X-ray machines. FMEA is employed to identify failure modes in the mobile X-ray machine. In the FMEA approach, one of the important terminologies is risk priority number (RPN). It is calculated by multiplying the scores of risk factors and is used to rank the various drive failure modes. When applied to a real situation, like in the present research problem, it was observed that RPN has a set of limitations. For example, RPN multiplies Severity (S), Occurrence (O), and Detection (D) equally, assuming all three are equally important, which may not reflect the actual risk impact. Different S, O, and D combinations can result in the same RPN but may represent very different risk profiles (e.g., S = 10, O = 1, D = 10 v/s S = 5, O = 5, D = 4; both give RPN = 100). Therefore, to assess and rank the risk of failure modes and overcome some of the limitations of RPN, a modified and integrated FMEA model based on the analytic hierarchy process (AHP) and hierarchical technique for order of preference by similarity to the ideal solution (TOPSIS) method is adopted in the present study. The modified methodology adopted in the present study involves generating the weights among risk factors from the AHP technique, and the scores of failure modes concerning risk factors are obtained using the conventional RPN approach. Further to illustrate the effectiveness and efficiency of the modified FMEA method of the present study, an example using FMEA to illustrate the Rank of the Drives-related failure in a Mobile X-ray machine is provided. Finally, an exhaustive comparative analysis is conducted to demonstrate the benefits of the new method over previous multiple attribute decision-making (MADM) methods, and a sensitivity analysis is undertaken to investigate the effects of the weights of risk factors.