Kusmiadi, Asep Kusmiadi (2026) Productivity-Centered Spares Part: Kebijakan Persediaan Berbasis Risiko Untuk Memaksimalkan Produksi Energi Listrik Dengan Meminimalkan Downtime. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pengelolaan persediaan suku cadang pada pembangkit listrik umumnya masih menggunakan pendekatan service level yang berfokus pada tingkat ketersediaan material tanpa mempertimbangkan dampak kehilangan produksi energi akibat downtime. Pada sistem pembangkitan, beberapa komponen memiliki frekuensi kerusakan yang rendah namun dapat menyebabkan kehilangan produksi energi yang signifikan apabila suku cadangnya tidak tersedia. Kondisi ini menyebabkan kebijakan persediaan yang hanya berbasis histori permintaan belum sepenuhnya mampu mendukung produktivitas pembangkit secara optimal. Penelitian ini mengusulkan suatu kebaruan berupa integrasi Reliability, Availability dan Maintainability (RAM)/Survival analysis, penilaian kritikalitas berbasis dampak kehilangan produksi energi listrik dalam satuan Giga Watt Hour (GWh), kebijakan persediaan berbasis risiko ke dalam satu kerangka produktivitas terpadu untuk pengelolaan suku cadang pada sistem pembangkitan tenaga listrik. Penilaian kritikalitas dilakukan menggunakan metode Analytical Hierarchy Process (AHP) dengan kriteria GWh impact, safety, compliance, serta TTR dan substitusi. Selanjutnya, komponen diklasifikasikan ke dalam strategi persediaan bertingkat. Evaluasi kinerja kebijakan dilakukan melalui simulasi Monte Carlo dengan membandingkan skenario baseline dan skenario Productivity-Centered Spares Part pada sistem pembangkitan PT. XYZ. Pendekatan ini dikembangkan untuk menjawab keterbatasan kebijakan persediaan konvensional yang masih berorientasi pada service level dan belum secara eksplisit memperhitungkan dampak kehilangan produksi energi dan downtime pembangkit. Hasil penelitian menunjukkan bahwa seluruh komponen yang dianalisis memiliki pola permintaan intermittent, sehingga tidak tepat apabila kebijakan persediaan hanya didasarkan pada rata-rata pemakaian historis. Hasil pembobotan kritikalitas menunjukkan bahwa Generator PLTD Tahuna Deutz, Generator PLTD Tahuna Mitsubishi, dan Deepsea 7310 termasuk dalam kelas kritikalitas tinggi karena memiliki konsekuensi besar terhadap produktivitas dan keandalan operasi. Hasil simulasi Monte Carlo menunjukkan bahwa penerapan PCS mampu menurunkan total stockout dari 0,80 menjadi 0,69 kejadian per replikasi, menurunkan total downtime dari 2.369,71 jam menjadi 2.229,31 jam, serta menurunkan total biaya gangguan dari Rp. 4.240.095.187 menjadi Rp. 3.848.603.683. Secara keseluruhan, pendekatan PCS menghasilkan penurunan stockout sebesar 13,75%, downtime sebesar 5,92%, dan biaya gangguan sebesar 9,23% dibandingkan skenario baseline. Temuan ini menunjukkan bahwa integrasi aspek produktivitas dan kritikalitas aset dalam pengambilan keputusan persediaan dapat meningkatkan efisiensi biaya sekaligus mendukung keberlangsungan produksi energi.
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This study proposes a novel integration of Reliability, Availability, and Maintainability (RAM)/survival analysis, criticality assessment based on the impact of electrical energy production loss in Giga Watt Hours (GWh), and risk-based inventory policy into a unified productivity-oriented framework for spare parts management in power generation systems. Criticality assessment is conducted using the Analytical Hierarchy Process (AHP) with four criteria: GWh impact, safety, compliance, and TTR and substitution. Furthermore, the components are classified into tiered inventory strategies, namely maximum protection, high protection, controlled stock, and efficient minimum stock. The policy performance is evaluated through Monte Carlo simulation by comparing the baseline scenario and the Productivity-Centered Spares Part scenario in the PT. XYZ power generation system. This approach is developed to address the limitations of conventional inventory policies, which are still oriented toward service level and do not explicitly consider the impact of energy production loss and power plant downtime. In this context, the value of a spare part is not determined solely by its usage frequency, but also by its contribution to preventing energy production loss and reducing downtime duration. The results show that all analyzed components have intermittent demand patterns. Therefore, inventory policies should not be based solely on historical average consumption. The criticality weighting results indicate that the Deutz Generator of PLTD Tahuna, the Mitsubishi Generator of PLTD Tahuna, and Deepsea 7310 are classified as high-criticality components because they have significant consequences for productivity and operational reliability. The Monte Carlo simulation results show that the implementation of PCS reduces total stockout from 0.80 to 0.69 occurrences per replication, decreases total downtime from 2,369.71 hours to 2,229.31 hours, and lowers total disruption cost from IDR 4,240,095,187 to IDR 3,848,603,683. Overall, the PCS approach reduces stockout by 13.75%, downtime by 5.92%, and disruption cost by 9.23% compared with the baseline scenario. The findings of this study indicate that an inventory policy applying the PCS framework with a productivity improvement orientation is more relevant for implementation in the power generation industry. By integrating inventory stock decisions with productivity improvement through downtime reduction to minimize electrical energy production losses, the PCS approach can provide a solution for determining spare parts priorities in a more proportional manner according to the operational consequences of each component.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Peningkatan produktivitas, downtime, suku cadang, RAM analisis, monte carlo, Productivity Improvement, downtime, spare parts, RAM analysis, monte carlo. |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD30.23 Decision making. Business requirements analysis. T Technology > T Technology (General) > T57.62 Simulation T Technology > T Technology (General) > T58.62 Decision support systems T Technology > T Technology (General) > T58.8 Productivity. Efficiency |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26101-(S2) Master Thesis |
| Depositing User: | Asep Kusmiadi |
| Date Deposited: | 22 Jul 2026 04:13 |
| Last Modified: | 22 Jul 2026 04:13 |
| URI: | http://repository.its.ac.id/id/eprint/136162 |
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