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All Journal Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Tri Baktiono
PT Angkasa Pura Indonesia
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering

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Analisis Reliability, Availability, dan Maintainability (RAM) Airfield Lighting System Berbasis Data Logbook Pemeliharaan Bandar Udara Direstu Amalia; M. Indra Martadinata; Yayuk Suprihartini; Dwi Lestary; Tri Baktiono; Yusuf Aldila Pradana Kusuma; Bahder Johan; Masayu Nabila Zahira; Nadya Safwah
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 4 No. 5 (2026): September : Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Inf
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v4i5.1545

Abstract

This study models Reliability, Availability, and Maintainability (RAM) parameters of the Airfield Lighting System (ALS) at Sultan Mahmud Badaruddin II International Airport, Palembang, as part of a first-stage basic research agenda on human-factors-based ALS maintenance management. Using a qualitative case study approach, disruption data were extracted from 18 verified logbook entries recorded between January and June 2026, covering nine ALS subsystem groups. Mean Time Between Failures, Mean Time To Repair, and Inherent Availability were calculated using two complementary methods: a strict regulatory method based on interrupted operational hours, and a workload-proxy method based on start-to-finish repair duration. The two methods produced markedly different Mean Time To Repair values, reflecting distinct constructs of operational impact and maintenance effort. Findings show that the ALS maintains a very high service availability, while the Approach Lighting subsystem accounts for the largest share of repair workload and the Runway Threshold/End Lighting subsystem shows the highest failure rate per installed unit. These results identify priority subsystems for preventive maintenance and provide an empirical foundation for the subsequent integration of human factors analysis into the ALS maintenance management framework.
Co-Authors Amalia, Direstu Bahder Johan Dwi Lestary Martadinata, M Indra Masayu Nabila Zahira Nadya Safwah Yayuk Suprihartini Yusuf Aldila Pradana Kusuma