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Reliability Analysis and Maintenance Optimization of Projection Spot Welding Machine in the Automotive Industry

Volume 14, Number 8, August 2018, pp. 1833-1841
DOI: 10.23940/ijpe.18.08.p20.18331841

Ulugbek Fayzimatov, Buyun Sheng, Zheng Xiao, and Ismael Toure

Wuhan University of Technology, Wuhan, 430000, China

(Submitted on April 30, 2018; Revised on June 13, 2018; Accepted on July 18, 2018)

Abstract:

This study analyzed the operational characteristics of the reliability and maintainability of the Projection Spot Welding (PSW) machine in the automotive industry. The components of the machine were grouped into three sub-systems: electrical, pneumatic, and hydraulic, and they were ordered into a hierarchical structural model for calculating reliability characteristics. The obtained maintenance lists and failure and repair data were studied and classified. Trend and serial correlation tests were carried out to select a proper modeling technique for each sub-system. Then, the reliability-maintainability model was constructed to estimate the failure behavior of the sub-systems, identify the best-fit distribution model, and calculate reliability characteristics. Finally, based on the calculated reliability characteristics, the preventive maintenance intervals for a different reliability level were calculated and requirements for increasing reliability were suggested. The analysis of the main structural sub-systems of the RSW machine showed that the hydraulic sub-system significantly affects the overall reliability level of the machine. However, the mean time to repair (MTTR) of the hydraulic sub-system is the lowest among other sub-systems. The analysis also found that the reliability of the electric and pneumatic sub-systems decreases by up to 50% after approximately 80h and 40h, respectively. The results of the study concluded that the reliability and maintainability analysis can improve the accuracy of preventive maintenance intervals and assess the reliability of each component of the RSW machine, which in turn can help reduce operating costs and extend the life of machine components.

 

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