Implementing Risk-Based Maintenance Strategies for Distributed Control System as Power Plant Asset Management

• Published in: IOP conference series. Materials Science and Engineering Vol. 1096; no. 1; p. 12108
• Main Authors: Yulianto, D T, Isman, R M, Ihsan, S N, Susanto, H G
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.03.2021
• Subjects: Asset management; Control systems; Distributed control systems; Electric power distribution; Gas turbines; Mathematical analysis; Plant reliability; Power plants; Preventive maintenance; Reliability aspects; Risk levels; Risk management; Steam turbines
• ISSN: 1757-8981; 1757-899X; 1757-899X
• DOI: 10.1088/1757-899X/1096/1/012108

The electricity generated from the power plant is subject to several requirements for active power, voltage, and frequency according to the grid system, so the machine must be controlled to achieve requirement by a power plant control system knows as Distributed Control System (DCS). DCS system in block 1 Muara Tawar power plant using Procontrol P-13 for gas turbine and Procontrol P-14 to control steam turbine. These systems had operated since 1997 and had been nearly operating for 23 years until now, and several failures tend to increase from time to time. The failures of the DCS and the lack of control cards will result in the loss of production. DCS system assets must handle properly to maintain the overall reliability of the power plant system. A method and strategy to maintain DCS must be carried out and ensure reliability and risk always under controlled conditions. Implementing Risk-based maintenance by carrying out quantitative calculations through the reliability approach and the level of the consequence of failure to calculate equipment risk is one of the methods of the DCS system. The result of Risk-based maintenance method shows the highest risk on risk map of the DCS system was in cubicle 14CBA02, 14CBA03 with a high-risk level and gas turbine and HRSG cubicle in medium-high level. The interval preventive maintenance time calculated by reliability within a year showed that cubicles 14CBA02 and 14CBA03 suggested to be maintenance every 29 days to reduce possibilities to failure.