In recent years, the reliability-centered maintenance (RCM) model has gained increasing attention in engineering practice. As an efficient maintenance strategy, preventive maintenance can maintain the reliability and safety of equipment with minimal resource consumption, and plays an important role in the industrial field.
Traditional reliability analysis methods usually rely on a large amount of life test data to improve the assessment accuracy by using life data as an information source. However, with the rapid development of science and technology, the reliability of modern products has been significantly improved and the average life span has been greatly extended, resulting in life-related data becoming more and more difficult to obtain.
It is worth noting that performance degradation is an inevitable process of product failure and a natural property of materials and structures that evolve over time. Even for highly reliable products, performance degradation information (e.g., wear and tear, parameter drift, etc.) can be obtained through monitoring, regardless of whether or not a functional failure has occurred. These degradation data not only reflect the pattern of change of product performance parameters, but also imply the correlation between performance and reliability. Therefore, even if there is a lack of direct life data, it is still possible to analyze the degradation data to explore the life characteristics of the product information.
Based on this characteristic, if the performance degradation data can be used as the research basis, combined with reasonable preventive maintenance strategy, a more accurate overhaul life prediction model can be established to provide a scientific basis for maintenance decision-making.
 

Preventive Maintenance,Overhaul Life,Reliability,Maintenance Strategy,Performance Degradation