Condition-Based Monitoring for Prompt Identification of Component Failures to Safeguard the Entire System.

Condition-based monitoring (CBM) has emerged as a transformative approach in predictive maintenance, enabling the proactive identification of potential component failures. It offers numerous advantages like Cost Savings, Increased Equipment Lifespan, RCA of failed parts, Optimized Resource Utilization, Reduced Disruptions, Enhanced Reliability and Safety and many more making it a vital approach for effective maintenance and operational efficiency. This paper presents a comprehensive methodology for monitoring and analyzing vibration trends to predict and prevent the breakdown of critical components in IC Engine in its testing phase. The good part here is that this methodology is not just limited to IC Engine but can be applied across wide range of industries and mechanical systems as from the literature and past vibration data, it was observed that before any such failure engine vibration increases. If the engine is stopped at that moment, it can be preserved, allowing for further investigation to be conducted. During the engine reliability development process, failures in the crank train and valve train can result in damage to multiple components, making it challenging to analyze the sequence of failure and identify the initial cause and root problem. By employing advanced vibration analysis techniques, the study aims to detect anomalies indicative of wear, misalignment, or other precursors to failure. This research contributes to the growing body of knowledge in CBM, offering a scalable and adaptable framework for implementing vibration-based predictive maintenance across diverse industrial applications. The proposed methodology not only enhances reliability but also supports sustainable maintenance practices by minimizing resource wastage and ensuring timely interventions.