Risk Condition Based Decision Making and Maintenance Tasks Optimization Research

摘要

Downtime of rotating equipment in large petrochemical plants often led to serious or even disastrous safety and environmental accidents, which generally stem from inadequate maintenance or incapability of failure prediction. In order to rationally allocate maintenance resources and improve the reliability, availability and safety of equipment, a kind of risk & condition based decision-making model is established in this paper. Using real time database, web service and Service Oriented Architecture (SOA), a data framework is developed to provide a unified data structure and man-machine interface, which integrates reliability-centered maintenance (RCM), condition monitoring system (CMS) and manufacturing executive system (MES) together. Based on RCM and condition monitoring, the risk rank and degradation trend of failure characteristics are used to support the decision-making and to optimize maintenance tasks. The result of an engineering case shows that the maintenance strategy based on the risk assessment and condition monitoring can lower the operational risk while enhancing the reliability, availability and safety. Experiences show that the key factors affecting the successful transition to a more risk & condition informed approach must be based on the firm support from both managers and engineers. Meanwhile, it is very crucial that engineers, operators and maintenance staffs receive proper education.