International Journal on Advanced Science, Engineering and Information Technology, Vol. 12 (2022) No. 4, pages: 1673-1681, DOI:10.18517/ijaseit.12.4.15277

Using Failure and Repair Data for System Improvement in Plant Facilities

Rahmat Nurcahyo, Riyan Nuryanto, Hendri Dwi Saptioratri Budiono, Muhammad Habiburrahman, Ellia Kristiningrum

Abstract

Previous research has emphasized the need to identify the cooling tower's critical components and parts in order to evaluate the system's performance. From a reliability point of view, a cooling tower is considered a series system. There is a redundant unit for some equipment to maintain availability and ensure the equipment carries out its intended function. The main objective of this study is to identify the critical component or parts of the cooling tower and evaluate system performance. Based on a scientific way: reliability, availability, and maintainability (RAM) analysis, the critical component of a cooling tower is investigated using RAM prediction indices. This paper deals with a case study conducted in a cooling tower plant. Both ERP extracted files, and maintenance log-book have been confirmed to maintenance personnel and maintenance monthly report to verify failure event and repair time. According to the results, the system performance (cooling tower) of the system availability is 93.91 percent. There is still an opportunity for a 6.09 percent system performance increase to be implemented on critical subsystems. The emphasis of crucial subsystem maintenance will be solely on the weakest components. Pareto charts and RAM analysis show that pump performance should be prioritized on essential components, such as packing seals or grand packing. The performance results obtained by upgrading are predicted to be 95.6725 percent. This paper proposes a method for identifying the weakest component or part based on failure and repair data. The weakest component will be the focus of future system performance improvements.

Keywords:

Cooling system; reliability; availability and maintainability analysis; system improvement; system performance.

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