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All Journal Syntax Literate: Jurnal Ilmiah Indonesia Indonesian Journal of Chemistry Eksakta : Berkala Ilmiah Bidang MIPA Journal of Materials Exploration and Findings
Fatriansyah, Jaka Fajar
Department Of Metallurgical And Materials Engineering, Faculty Of Engineering, Universitas Indonesia, Kampus Depok, West Java 16424, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Perancangan Program Pengestimasi Probabilitas Kegagalan Peralatan Penukar Panas Akibat Korosi Seragam Berbasis Deep Neural Network Fatriansyah, Jaka Fajar; Dhaneswara, Donanta; Hanifa, Muthia; Hartoyo, Fernanda; Pradana, Agrin Febrian; Anis, Muhammad; Fauzi, Andrian
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.943 KB) | DOI: 10.36418/syntax-literate.v8i3.11486

Abstract

Meningkatnya standar keamanan dan ketatnya persaingan antar perusahaan meningkatkan kebutuhan bagi suatu perusahan untuk mengendalikan kegagalan pada peralatan. Inspeksi secara teratur dilakukan sebagai bagian dari rangkaian pemeliharaan dan manajemen integritas peralatan. Dalam merencanakan dan melakukan inspeksi, diperlukan strategi yang tepat agar inspeksi yang dilakukan tepat sasaran dan sesuai dengan kebutuhan. Risk-based inspection merupakan teknik pengambilan keputusan dalam perencanaan pemeliharaan yang berdasar pada risiko. Pada saat ini, penggunaan metode-metode kecerdasan buatan untuk kegiatan penilaian risiko, pemodelan konsekuensi, dan perencanaan pemeliharaan telah dilakukan. Penelitian ini bertujuan untuk mengembangkan suatu program yang memanfaatkan pembelajaran mesin dan kecerdasan buatan untuk melakukan penilaian salah satu komponen risiko yaitu probabilitas kegagalan (Probability of Failure, PoF) pada bagian cangkang dalam peralatan penukar panas menggunakan deep learning. Model ini dapat membantu operator yang bekerja di bidang minyak dan gas untuk menentukan tingkatan risiko sehingga inspeksi dapat dilakukan dengan lebih efisien dan terarah. Penelitian ini menghasilkan sebuah program dan disain program pembelajaran mesin berbasis deep learning yang digunakan untuk memprediksi risiko kegagalan akibat korosi seragam pada peralatan sisi dalam cangkang peralatan penukar panas cangkang dan buluh (shell-and-tube heat exchanger) berdasarkan standar API 581 dengan akurasi sebesar 89% yang didapatkan dengan parameter-parameter diantaranya learning rate sebesar 0.001, epoch sebesar 150, random state sebesar 60, tiga hidden layer, dan test size sebesar 0.2.
Analysis Risk Based Inspection API 581 on LPG Spherical Tank at PT. XYZ Trahmawan, Sigit; Siradj, Eddy Sumarno; Fatriansyah, Jaka Fajar
Journal of Materials Exploration and Findings Vol. 3, No. 2
Publisher : UI Scholars Hub

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Abstract

Liquified petroleum gas (LPG) spherical tanks are pressure vessel equipment for storing fuel gas products. The high pressure along with the fuel gas inside as flammable and combustible substance means that this equipment might result major accident hazard such as explosion, fires and environmental pollution. This study is aimed calculated and mitigate risk on 500 metric ton capacity LPG spherical tank using Risk-based inspection (RBI) analysis method that makes risk as its foundation. This RBI method uses quantitative analysis referring to API 581 to determine the risk of LPG Spherical Tank by determining the probability of failure (PoF) and the consequences of failure (CoF). From the results of the risk assessment will be determined appropriate methods and scheduling inspection for LPG spherical tank. As result, thinning defect mechanism is one that influences the possibility of failure of LPG ball tank equipment with a failure rate of 4.13 E-06 failure/year. The result risk assessment of LPG ball tank is at the medium-high risk level with the probability of failure being in category 1 (low) and the consequence of failure being in category E (high). Meanwhile, the recommended inspection method for LPG tank is internal and external inspection in the form of visual examination and ultrasonic thickness measurement with an inspection interval every 5 (five) years.
A Comparative Study of Conventional and Statistically Active Corrosion Methods for Corrosion Growth Assessment of a 24-inch Gas Pipeline Rinaldi, Rudi; Fatriansyah, Jaka Fajar
Journal of Materials Exploration and Findings Vol. 3, No. 3
Publisher : UI Scholars Hub

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Abstract

Component failures in oil and gas pipelines can have fatal consequences, leading to operational downtimes and environmental damage. Knowledge of the corrosion growth rate is fundamental to pipeline integrity management, as it is essential for risk assessment and decisions related to asset management. This article aimed to compare two approaches for the corrosion growth estimation of the 24-inch offshore gas pipeline: the conventional method versus the Statistically Active Corrosion (SAC) method. This article is based on the in-line inspection (ILI) results of two consecutive assessments from 2020 to 2023 of the entire 73 km of the pipeline. The results show that the SAC method evaluates the corrosion activity on the pipeline with better accuracy and localization than the conventional method, highlighting 782 corrosion active joints in the 5,987 pipeline joints. The SAC method leads to much higher average and maximum corrosion growth rates while also being able to pinpoint active corrosion locations more accurately. Thus, the SAC method is an efficient and simple strategy to cope with corrosion assessment problems regarding pipeline integrity management. It enables the operators to prioritize their maintenance actions, improving pipeline safety.
Co-Authors Arbi Irsyad Fikri Asral, D. Rizal Candraningrum, Veronica Hesti Dedi Supriadi Dhaneswara, Donanta Digita, Farhan Rama Dwira, Surya Eddy S Siradj Elvi Kustiyah Erlina, Linda Fadillah Fadillah Fadillah Fadillah Fauzi, Andrian Federico, Andreas Hanifa, Muthia Hanindito Haidar Satrio Hartoyo, Fernanda Jana Hafiza Linda Erlina Linuwih, Baiq Diffa Pakarti Mas'ud, Imam Abdillah Mochamad Chalid Muhammad Anis, Muhammad Muhammad Joshua Yuriansyah Barmaki Nafisah, Helya Chafshoh Nurullia, Zahra Nadia Ovelia, Hanna Paramita, Rafika Indah Pradana, Agrin Febrian Rafika Indah Paramita Ridzuan, Abdul Rahim Rudi Rinaldi, Rudi Salma Ilmiati Surip, Siti Norasmah Surya Dwira Tihara, Irma Hartia Trahmawan, Sigit Wan Jaafar, Wan Nor Raihan Windy Dwininda