OPTIMIZING MAINTENANCE FREQUENCY ON INSTRUMENTATION WITH THE RELIABILITY CENTERED MAINTENANCE METHOD AT PT X
DOI:
10.54443/morfai.v5i6.4514Published:
2025-11-25Downloads
Abstract
In facing maintenance challenges in offshore oil and gas operational platforms, determining instrumentation components based on Safety and Environment Critical Element (SECE) with the Reliability Centered Maintenance (RCM) method requires component repair data in the 2019-2023 time interval. So far, maintenance intervals have been carried out conventionally without considering historical reliability data, which has led to over-maintenance and under-maintenance. This study aims to optimize the maintenance frequency of SECE instrumentation with the RCM approach to improve technical, operational, and economic efficiency, as well as ensure compliance with safety and environmental standards. The methodology used includes data collection, technical document analysis, reliability calculations, and the development and re-implementation of maintenance work in the system. The calculation results show that several instruments have a high level of reliability, such as the pressure transmitter at 99.86%, while the shutdown valve recorded the lowest reliability of 97.86%, which based on a significance test can be extended to a 12-month maintenance interval. Optimizing the maintenance interval resulted in a significant reduction in man-hour requirements, up to 27% on the entire platform while maintaining system reliability. Technical recommendations were also proposed, including the use of statistical approaches such as the Weibull distribution for further analysis. This research shows that a data-driven RCM approach not only improves system reliability but also resource efficiency and overall occupational safety.
Keywords:
Reliability Maintenance Frequency InstrumentationReferences
Almeida, J. R., & de Almeida, A. T. (2012). A decision model for establishing optimal maintenance periods for industrial instruments. In Proceedings of the 2012 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1202–1206). IEEE.
American Petroleum Institute (API). (2016). API Recommended Practice 551, Fourth Edition: Process Measurement Instrumentation. API.
Baybutt, P. (2013). Risk tolerance criteria and the IEC 61511/ISA 84 standard on safety instrumented systems. Process Safety Progress, 32(3), 307–310. [https://doi.org/10.1002/prs.11554](https://doi.org/10.1002/prs.11554)
Devore, J. L. (2015). Probability and Statistics for Engineering and the Sciences (9th ed.). Cengage Learning.
Ebeling, C. E. (1997). An introduction to reliability and maintainability engineering (3rd ed.). Waveland Press.
Forest, J. J. (2018). Know your limits. Process Safety Progress, 37(4), 498–501. [https://doi.org/10.1002/prs.12000](https://doi.org/10.1002/prs.12000)
International Society of Automation (ISA). (2017). Technical Report ISA-TR18.2.4-2017 (R2022): Technical report for alarm systems for installed field instrumentation (pressure, temperature, level, and flow switches/transmitters). ISA.
Kececioglu, D. (1991). Reliability engineering handbook (Vols. 1–2). Prentice-Hall.
Li, F., & Brown, R. E. (2004). A cost-effective approach of prioritizing distribution maintenance based on system reliability. IEEE Transactions on Power Delivery, 19(1), 439–441. [https://doi.org/10.1109/TPWRD.2003.820411](https://doi.org/10.1109/TPWRD.2003.820411)
Montgomery, D. C. (2019). Introduction to statistical quality control (8th ed.). John Wiley & Sons.
Moubray, J. (1992). Reliability centered maintenance (2nd ed.). Industrial Press.
Mugarza, I., Flores, J. L., & Montero, J. L. (2020). Security issues and software updates management in the industrial internet of things (IIoT) era. Sensors, 20(24), 7160. [https://doi.org/10.3390/s20247160](https://doi.org/10.3390/s20247160)
Ramos, P. L., Nascimento, D. C., Cocolo, C., et al. (2018). Reliability-centered maintenance: Analyzing failure in harvest sugarcane machine using some generalizations of the Weibull distribution. Modelling and Simulation in Engineering, 2018, 1–12. [https://doi.org/10.1155/2018/1241856](https://doi.org/10.1155/2018/1241856)
Rizkya, I., Siregar, I., Siregar, K., et al. (2019). Reliability centered maintenance to determine priority of machine damage mode. E3S Web of Conferences, 125, 22005. [https://doi.org/10.1051/e3sconf/201912522005](https://doi.org/10.1051/e3sconf/201912522005)
Shah, M. H., & Agashe, S. D. (2016). Review of level measurement technologies with case study of level transmitter failure in natural gas processing plant. International Journal of Innovative Research in Science, Engineering and Technology, 5(5), 7305–7313.
Souza, J. A. L. d., Fo, D. J. S., Squillante, R., Junqueira, F., et al. (2014). Mitigation control of critical faults in production systems. IFIP Advances in Information and Communication Technology, 119–128. [https://doi.org/10.1007/978-3-642-54734-8_14](https://doi.org/10.1007/978-3-642-54734-8_14)
Squillante, R., Fo, D. J. S., Souza, J. A. L. d., et al. (2013). Safety in supervisory control for critical systems. IFIP Advances in Information and Communication Technology, 261–270. [https://doi.org/10.1007/978-3-642-37291-9_28](https://doi.org/10.1007/978-3-642-37291-9_28)
Stauffer, T., & Chastain-Knight, D. (2020). Do not let your safe operating limits leave you S-O-L (out of luck). Process Safety Progress, 40(1). [https://doi.org/10.1002/prs.12163](https://doi.org/10.1002/prs.12163)
Zhang, Y., Gautam, R., Zavala-Araiza, D., et al. (2019). Satellite-observed changes in Mexico’s offshore gas flaring activity linked to oil/gas regulations. Geophysical Research Letters, 46(3), 1879–1888. [https://doi.org/10.1029/2018GL081145](https://doi.org/10.1029/2018GL081145)
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Copyright (c) 2025 Mochammad Resha, Eko Wahyu Saputra, Chandra Salim
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