ABSTRACT
ABSTRACT: A methodology is developed for the identification of Energy-Intensified Equipment (EIE) for reliability analysis in the chemical processing industry. There are several methods based on classification that can be used for identifying such equipment, such as Always Better Control/ABC, Vital/Essential/Desirable (VED), Scarce/Difficult/Easily available (SDE), High/Medium/Low (HML), and Fast/Slow/Non-moving (FSN), but these selective inventory control methods do not indicate the criticality of an item. The damage grounds from failure and the failure modes to plan an optimum maintenance program. The method is applicable in understanding the equipment in the operational phase where there is only limited data available. When available data is scarce or generic, critical data is retrieved from some related selective inventory data banks. In this method, based on physical factors, the situation under which the equipment is working, such as external/internal load/pressure, is used in modeling the equipment. Pareto’s 80/20 principle is employed to identify its criticality and calculate its risk factor. The current methodology applies criticality importance analysis and criticality allocation to optimize the maintainability correlated with Reliability-Centered Maintenance (RCM) models. Evaluating the reliability of life-threatening equipment in reverse engineering of the (competitive) operational phase is one of the applications of this method. As a case study, EIE is used for assessment of the proposed method and the results identify the equipment and sub-systems that are critical elements from a reliability and maintenance perspective. A benchmark of the results indicates the effectiveness and quality of the method in identification of energy-intensified equipment for reliability analysis.
