Critical Analysis of Machine Condition Monitoring by Using Risk Priority Number and Analytical Hierarchy Process

Reliability of the whole plant can be predicted by the condition of system machines and components. For this purpose, various condition monitoring methods like visual monitoring, performance monitoring, wear particle analysis by ferrography, etc., can be used effectively based on the applications. By these methods, information about forthcoming failures can be available well in advance which can reduce chances of failure as well as hazardous effects on the plant and on society also. For this purpose, reliability study of vacuum drying plant was done. It includes subsystems which are vacuum pumping, heating, autoclave, scavenging and air circulation. Real site data have been used for this purpose. The present study involves understanding the functions of overall systems in plant and equipment having interdependent relationship in the manner of specific configuration and draws the reliability block diagram down to the component level based on testing or field data. Basic faults were found out by using failure mode effect analysis (FMEA) for calculation of reliability. Analyzing causes and effects of failure in each subsystem and making critical analysis of the subsystem ranking of the critical components have been carried out by risk priority number (RPN) and by using analytical hierarchical process (AHP).