Optimasi Preventive Maintenance Pada Shipping Pump Dengan Genetic Algorithm Di Joint Operating Body Pertamina-Petrochina East Java (Job P-Pej) Soko – Tuban

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 ============================================================================================ 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.
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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