Predictive Maintenance Analysis In Predicting Equipment Damage In Balance Of Plant (BOP) Area (Pangkalan Susu Power Plant Case Study)

  • Tri Satria Tegar Universitas Pembangunan Panca Budi
  • Solly Aryza Universitas Pembangunan Panca Budi
  • Hamdani Universitas Pembangunan Panca Budi
Keywords: Power Plant, Maintenance, Predictive Maintenance, Vibration Meter, Thermography, Demineralized Pump

Abstract

Along with the increasing demand for electricity use in Indonesia, especially north Sumatra, PT. PLN (PERSERO) built a coal-fired steam power plant. With the existence of this steam power plant, it can help the country's electricity supply, especially in Sumatra. As is known that steam power plants are plants that have a high potential for equipment damage, especially the Balance of Plant (BOP) area. Therefore, a team is formed that can overcome and identify equipment damage with certain tools, called the Predictive Maintenance team. Predictive Maintenance (PdM) techniques are designed specifically to help determine the condition of equipment assets used as a reference for predictions for when asset maintenance activities should be carried out. Predictive Maintenance (PdM) is a form of maintenance that directly monitors the condition and performance of equipment during normal operation to reduce damage or failures in the future. The main tools used for Predictive Maintenance are Vibration Meter and Infrared Thermography. And the equipment has standards or limits resulting from trending measurement data and also has international standards as a reference. There was damage to one of the Balance of Plant (BOP) equipment, which is Demineralized (DM) Pump that causes the supply of demineralized water to the unit to be reduced and the unit load cannot be increased to maximum. With predictive maintenance (PdM) analysis, it can be quickly identified that the damage was in the drive end (DE) motor bearing of the demineralized equipment (DM) pump. Replacement of bearing on the Demineralized motor (DM) can maximize the performance of the unit so as to make an electrical energy saving of 1,095,360 kWh. In addition, it also has financial benefits of Rp. 681,781,917,-

Downloads

Download data is not yet available.

References

Bachtiar.Hedralius. (2015). Program Pendampingan Percepatan Kompetensi. Langkat.

Corporation, G. P. (2014). Power Plant Maintenance and Repair Part. Langkat: Xiaoning Wang.

Corporation., G. P. (2014). Power plant Operation Asset Medan : PLTU 2 X 200 MW. Langkat.

Marbun, A. g. (2016). Realibility dan Control PLTU PNS OMU 2 x 200 MW. Langkat.

power, P. I. (2020). Asset Management Demineraliz Pump no. 2. Langkat, Sumatera Utara, Indonesia.

Subiyantoro, P. (2018). Analisa Vibrasi dan Temperatur CBM PLTU Pangkalan Susu. Langkat.

University, P. C. (2015). Pengoperasian PL

A. Simangunsong and P. S. Hasugian, “Application of the Certainty Factor Method to Diagnose Escherichia Coli Bacteria in Refilled Drinking Water,” J. Info Sains Inform. dan Sains, vol. 10, no. 1, pp. 7–12, 2020.

C. Baturu, “Brute Force Algorithm Implementation Of Dictionary Search,” J. Info Sains Inform. dan Sains, vol. 10, no. 1, pp. 24–30, 202

Sihotang, “Analysis Of Shortest Path Determination By Utilizing Breadth First Search Algorithm,” J. Info Sains Inform. dan Sains, vol. 10, no. 2, pp. 1–5, 2020.

Published
2021-12-31
How to Cite
Tegar, T. S., Aryza, S., & Hamdani. (2021). Predictive Maintenance Analysis In Predicting Equipment Damage In Balance Of Plant (BOP) Area (Pangkalan Susu Power Plant Case Study). INFOKUM, 10(1), 490-497. Retrieved from https://infor.seaninstitute.org/index.php/infokum/article/view/337

Most read articles by the same author(s)

1 2 3 > >>