Enhancing Rotary Machine Reliability Through Condition-Based Maintenance Optimization
Keywords:Condition-based maintenance, rotary machine, optimization, reliability
AbstractRotary machines possess an inherent characteristic of generating vibrations, leading to the deterioration of critical components, particularly bearings and gears, ultimately failing the system. Vibration analysis is widely acknowledged as the predominant diagnostic technique employed for assessing the state of machinery and informing maintenance strategies. Condition-based maintenance (CBM) is a crucial component of proactive maintenance strategies that optimize machine availability by implementing timely interventions and minimizing costly breakdowns. This research endeavour aims to establish a comprehensive framework that enables evaluating the operational state of rotary machinery and its critical components, specifically emphasizing bearings. The interdependence between maintenance and machine health is evident, as a well-maintained machine requires minimal maintenance, while a machine undergoing deterioration requires immediate intervention. Rotary machines, which hold significant importance in various industrial processes, often face significant obstacles to bearing issues. These challenges lead to considerable disruptions in output and escalate maintenance costs. The current study examines the efficacy of CBM as a potential solution to the aforementioned issues. CBM is a maintenance strategy that utilizes real-time data on machine conditions to make informed decisions regarding maintenance interventions. By leveraging this approach, maintenance activities can be executed at the most opportune time, maximizing efficiency and effectiveness. CBM is a strategic approach that empowers enterprises to proactively mitigate failures, optimize maintenance schedules, and improve overall operational efficiency by accurately estimating the remaining usable life of machine components. This research study contributes to the growing body of knowledge on CBM, offering valuable insights into predictive maintenance and its potential to enhance the reliability and efficiency of rotary machinery.
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