Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)

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[This article belongs to Volume - 47, Issue - 01]

Abstract : In today's competitive market, business organizations must strive for escalating efficiency and optimize their manufacturing operations to confirm sustainability. To attain this, they need to ponder various factors to minimize the risks of machine failure and respond promptly to customer demands in a prompt manner. Our proposal focuses on predictability and real-time monitoring of machine deterioration, as well as the influence of the time value of money on any machines. Machines generally deteriorate over time, leading to production latency and hypothetically lower-quality products. In this article, we propose utilizing the Cox regression model to optimize factory benefits by employing proactive analytics and preventive maintenance, guaranteeing reliable quality in production at all times. This analysis will evaluate machine survival conditions and will be based on hazard and risk ratios.