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1- Industrial Engineering Institut Teknologi Adhi Tama Surabaya , lukmandono@itats.ac.id
2- Industrial Engineering, Institut Teknologi Adhi Tama Surabaya
Abstract:   (35 Views)
Gas Turbine Generators (GTGs) are critical assets that play a key role in ensuring the continuity of power generation in the oil and gas industry. The high frequency of failures in several GTG components during the 2021-2025 period has led to increased downtime and reduced system performance. This study aims to identify critical components, assess failure risks, and determine optimal preventive maintenance (PM) intervals using the Failure Mode and Effects Analysis (FMEA) and Reliability-Centered Maintenance (RCM) approaches. Actual GTG failure and maintenance data collected over a five-year period were used to support the analysis and validate the reliability-based PM optimization model. The FMEA results identified three critical components with the highest Risk Priority Numbers (RPNs): the Control System (320), Turbine (280), and Combustor (240). Reliability analysis was performed by evaluating the Mean Time Between Failures (MTBF), Mean Time To Repair (MTTR), availability, and reliability based on the Weibull distribution. The optimal PM intervals for individual components were determined to be 767 hours for the Control System, 662 hours for the Turbine, and 663 hours for the Combustor. Using a group maintenance strategy, these intervals were standardized to a common interval of 600 hours. The implementation of the 600-hour PM interval increased component reliability to 81.36%, 88.94%, and 71.23% for the Control System, Turbine, and Combustor, respectively, outperforming the existing 4,000-hour maintenance interval. These findings demonstrate that the proposed maintenance strategy can enhance system reliability while supporting operational continuity and production sustainability.
Full-Text [PDF 813 kb]   (14 Downloads)    
Type of Study: Research | Subject: Reliability and Maintenance
Received: 2026/06/23 | Accepted: 2026/11/3

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.