Asrori, Ahmad (2014) Optimasi Preventive Maintenance Pada Shipping Pump Dengan Genetic Algorithm Di Joint Operating Body Pertamina-Petrochina East Java (Job P-Pej) Soko – Tuban. Undergraduate thesis, Institut Teknologi Sepuluh Nopember Surabaya.
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Abstract
Proses pengiriman minyak mentah dari Central Processing
Area (CPA) ke Floating Storage Offloading (FSO) membutuhkan
unit shipping pump dengan head yang sangat tinggi. Berdasarkan
operation manual dari vendor, strategi pemeliharaan yang
direkomendasikan untuk unit shipping pump adalah Preventive
Maintenance (PM). Namun, karena dianggap kurang efisien,
maka PM dengan interval pendek dikurangi atau bahkan tidak
dilakukan oleh operator. Dari hasil analisis Overall Equipment
Effectiveness yang pernah dilakukan menunjukkan bahwa usaha
peningkatan efisiensi aktivitas PM dengan cara mengurangi
aktivitas PM yang seharusnya dilakukan justru menyebabkan
kualitas kinerja shipping pump menjadi tidak maksimal.
Dalam peneilitan ini dilakukan optimasi Preventive
Maintenance (PM) pada shipping pump PP-8400B di CPA JOB
P-PEJ menggunakan Genetic Algorithm (GA). Inti dari optimasi
ini yaitu pada komponen racor fuel filter, fuel filter separator,
coolant filter, dan air filter dilakukan PM secara bersamaan,
namun dengan jenis PM yang berbeda untuk menekan total cost
maintenance dan tetap memaksimalkan reliability system.
Sehingga dapat diperoleh PM yang lebih efisien tanpa harus
menurunkan kualitas kinerjanya.
Hasil penelitian menunjukkan bahwa hasil optimasi yang
dilakukan dapat menghemat total cost maintenance racor fuel
filter sebesar 16,41% dan fuel filter separator sebesar 26,77%
selama 1500 jam. Di sisi lain reliability terkecil secara sistem
selama 1500 jam diperoleh 0,7151 dan masing-masing komponen
sebesar 0,9158 untuk racor fuel filter, 0,9035 untuk fuel filter
separator, 0,8995 untuk coolant filter, dan 0,8264 untuk air filter
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The process of shipping crude oil from Central Processing
Area (CPA) into Floating Storage Offloading (FSO) requiring
shipping pump unit with very high head. Based on manual
operation from vendor, maintenance strategy that recommended
for shipping pump unit is Preventive Maintenance (PM). But,
because it reputed less efficient, so operator become cutting or
not executing PM with short interval. From Overall Equipment
Effectiveness analysis which has been made indicating that the
effort for upgrading efficiency of PM activities with cutting PM
activities which should be do exactly causing performance quality
become not maximal.
In this research made optimizing Preventive Maintenance
(PM), on shipping pump PP-8400B in the CPA JOB P-PEJ with
Genetic Algorithm (GA). The core of this optimization will be
executed PM simultaneously on the racor fuel filter, fuel filter
separator, coolant filter, and air filter, but with different PM
activities for minimizing total cost maintenance and maximizing
reliability of system. So, obtainable PM which more efficient
without must reducing its performance quality.
The result of this research show that optimizing can be
economized total cost maintenance of racor fuel filter 16.41% and
fuel filter separator 26.77% during 1500 hours. On the other
hand, the lowest reliability of system obtainable 0.7151 and for
each component obtainable 0.9158 for racor fuel filter, 0.9035 for
fuel filter separator, 0.8995 for coolant filter, and 0,8262 for air
filter.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSF 511.8 Asr o |
| Uncontrolled Keywords: | Preventive maintenance, genetic algorithm, racor fuel filter, fuel filter separator, coolant filter, air filter, reliability, dan total cost maintenance |
| Subjects: | Q Science > QA Mathematics > QA402.5 Genetic algorithms. Interior-point methods. T Technology > TA Engineering (General). Civil engineering (General) > TA169 Reliability (Engineering) |
| Divisions: | Faculty of Industrial Technology > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | EKO BUDI RAHARJO |
| Date Deposited: | 22 Sep 2020 07:00 |
| Last Modified: | 22 Sep 2020 07:00 |
| URI: | http://repository.its.ac.id/id/eprint/82018 |
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