Optimization of Gas Turbine Maintenance Scheduling in PLN Tanjung Datuk Pekanbaru
Abstract
This study discusses determining the optimal scheduling for maintenance of gas turbine engines in PLN Tanjung Datuk Pekanbaru. The optimal maintenance scheduling is done on critical components, namely turbine blade and AVR (Automatic Voltage Regulator) using Monte Carlo simulation. The optimal scheduling maintenance scenario is done by generating random numbers from MTTF (Mean Time To Failure) and MTTR (Mean Time To Repair) values and data validity testing. The results of research for optimal checking of turbine engines are once every 10 days with the reliability of turbine engines 43%. The optimal time for repairing a gas turbine in case of damage is 1.49 hours. The checking time for critical components of the turbine blade is 9 days and AVR of 12 days. The scenario of preventive maintenance is likely need special repair or replacement periodically that is 117 days for turbine blade components and 173 days for AVR.
##Keywords:##
MTTF, Maintenance scheduling, Gas turbine, Turbine blade, AVR
Published
Nov 30, 2020
How to Cite
NOFRI, Bambang; SUSILAWATI, Anita; ROMY, Romy.
Optimization of Gas Turbine Maintenance Scheduling in PLN Tanjung Datuk Pekanbaru.
Journal of Ocean, Mechanical and Aerospace -science and engineering-, [S.l.], v. 64, n. 3, p. 88-93, nov. 2020.
ISSN 2527-6085.
Available at: <https://isomase.org/Journals/index.php/jomase/article/view/217>. Date accessed: 28 may 2026.
doi: http://dx.doi.org/10.36842/jomase.v64i3.217.
References
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[17]. Candra, N.C, Susilawati, A, Herisiswanto and Setiady, W. (2017). Implementation of Total Productive Maintenance (TPM) to Improve Sheeter Machine Performance, MATEC Web Conf., Vol. 135, 00028, https://doi.org/10.1051/matecconf/201713500028.
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[19]. Hong, S., Li, H., and Wang, F. (2013). Maintenance Scheduling of Distribution System with Optimal Economy and Reability, Engineering, Vol. 5, pp: 14-18.
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[21]. Tuara, M.R., Susilawati, A and Romy (2017). Implementasi Total Productive Maintenance (TPM) pada Mesin Turbin di PLN Tanjung Datuk Riau. JOM Fakultas Teknik, Vol.5, No. 2.
[22]. Mardiansyah, R.F. (2018). Analisa Ekonomis Peralatan Pulverizer Untuk Optimalisasi Keandalan PLTU Dengan Simulasi Monte Carlo Dan Pendekatan Analisa Biaya Siklus Hidup (Studi Kasus: PLTU Rembang). Tesis. Program Pascasarjana Megister Teknik Industri Universitas Islam Indonesia.
[2]. Gupta, A. and Lawsirirat, C. (2006). Strategically optimum maintenance of monitoring enabled multi-component systems using continuous-time jump deterioration models, Journal of Quality in Maintenance Engineering, Vol. 12, No. 3, pp: 306-329.
[3]. Marquez, A.C and Heguedas, A.S. (2002). Models for maintenance optimization: A study for repairable systems and finite time periods, Reliability Engineering and System Safety, Vol. 75, No. 3, pp: 367-377.
[4]. Nicolai, R. P. and Dekker, R. (2008). Optimal maintenance of multi-component systems: a review, in Kobbacy, K. and Murthy, D. N. (eds.) Complex system maintenance handbook, Springer, London, pp. 263-286.
[5]. Briš, R. (2008). Parallel simulation algorithm for maintenance optimization based on directed Acyclic Graph, Reliability Engineering and System Safety, Vol. 93, No. 6, pp: 874-884.
[6]. Sharma, A., Yadava, G. and Deshmukh, S. (2011). A literature review and future perspectives on maintenance optimization, Journal of Quality in Maintenance Engineering, Vol. 17, No. 1, pp: 5-25.
[7]. Marseguerra, M., Zio, E. and Podofillini, L. (2002). Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation, Reliability Engineering and System Safety, Vol. 77, No. 2, pp: 151-165.
[8]. Yeh, T.M. and Sun, J.J. (2011). Preventive maintenance model with FMEA and monte carlo simulation for the key equipment in semiconductor foundries, Scientific Research and Essays, Vol. 6, No. 26, pp: 5534-5547.
[9]. Arab, A., Ismail, N. and Lee, L.S. (2013). Maintenance scheduling incorporating dynamics of production system and real-time information from workstations, Journal of Intelligent Manufacturing, Vol. 24, No. 4, pp: 695-695.
[10]. Lynch, P., Adendorff, K., Yadavalli, V.S.S. and Adetunji, O. (2013). Optimal spares and preventive maintenance frequencies for constrained industrial systems, Computers and Industrial Engineering, Vol. 65, No. 3, pp: 378-387.
[11]. Peng, Y., Dong M. And Zuo, M.J. (2010), Current status of machine prognostics in condition-based maintenance: a review, International Journal of Advanced Manufacturing Technology, Vol. 50, pp: 297-313.
[12]. Jong, H.S. and Hong, B.J. (2015). On condition based maintenance policy, Journal of Computational Design and Engineering, Vol. 2, No. 2, pp: 119-127, https://doi.org/10.1016/j.jcde.2014.12.006.
[13]. Beaurepaire, P., Valdebenito, M.A., Schuëller, G.I. and Jensen, H.A. (2012). Reliability-based optimization of maintenance scheduling of mechanical components under fatigue, Computer Methods in Applied Mechanics and Engineering, Vol. 221- 222, pp: 24-40.
[14]. Valdebenito, M.A. and Schuëller, G.I. (2010). Design of maintenance schedules for fatigue-prone metallic components using reliability-based optimization, Computer Methods in Applied Mechanics and Engineering, Vol. 199, No. 33-36, pp: 2305-2318.
[15]. Kiran, D.R. (2017). Reliability Engineering in Total Quality Management, Butterworth-Heinemann, Chapter 27, pp: 391-404, doi.org/10.1016/B978-0-12-811035.
[16]. Wu, S., Chen, L., Wu, Q. and Wang, Z. (2015). Linking component importance to optimisation of preventive maintenance policy, Reliability Engineering and System Safety. Vol. 146. 10.1016/j.ress.2015.10.008.
[17]. Candra, N.C, Susilawati, A, Herisiswanto and Setiady, W. (2017). Implementation of Total Productive Maintenance (TPM) to Improve Sheeter Machine Performance, MATEC Web Conf., Vol. 135, 00028, https://doi.org/10.1051/matecconf/201713500028.
[18]. Kim, J., Lee S. and Shin, H. 2013. Effective Task Scheduling for Embedded Systems Using Iterative Cluster Slack Optimization, Circuits and Systems, Vol. 4 No. 8, pp.: 479-488. doi: 10.4236/cs.2013.48063.
[19]. Hong, S., Li, H., and Wang, F. (2013). Maintenance Scheduling of Distribution System with Optimal Economy and Reability, Engineering, Vol. 5, pp: 14-18.
[20]. Hariyanto, B and Romy (2020). Maintenance Schedule Optimization for Turnaround Hot Gas Path Inspection of Gas Turbine in North Duri Cogeneration Plant Using Impact Method, Journal of Ocean, Mechanical and Aerospace -Science and Engineering, Vol. 64, No. 1, pp:25-33.
[21]. Tuara, M.R., Susilawati, A and Romy (2017). Implementasi Total Productive Maintenance (TPM) pada Mesin Turbin di PLN Tanjung Datuk Riau. JOM Fakultas Teknik, Vol.5, No. 2.
[22]. Mardiansyah, R.F. (2018). Analisa Ekonomis Peralatan Pulverizer Untuk Optimalisasi Keandalan PLTU Dengan Simulasi Monte Carlo Dan Pendekatan Analisa Biaya Siklus Hidup (Studi Kasus: PLTU Rembang). Tesis. Program Pascasarjana Megister Teknik Industri Universitas Islam Indonesia.
