Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Yoga Yulasmana
Faculty of Engineering, Universitas Nurtanio Bandung, Indonesia
Aerospace Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Weibull Reliability Modeling with Right-Censored Data and Age-Replacement Optimization for IDG on Boeing 737-900ER Yoga Yulasmana; Beni Barliansah
Journal of Ocean, Mechanical and Aerospace -science and engineering- Vol 70 No 1 (2026): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Publisher : International Society of Ocean, Mechanical and Aerospace -scientists and engineers- (ISOMAse)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36842/jomase.v70i1.593

Abstract

This paper develops a Weibull-based reliability model for the Integrated Drive Generator (IDG) installed on Boeing 737-900ER aircraft operated in Indonesian low-cost carrier conditions. Time-to-removal is modeled on a Flight Hours (FH) exposure scale and explicitly incorporates right-censored observations using Maximum Likelihood Estimation (MLE). The estimated Weibull shape parameter (?= 3.308 and ? = 7261 FH) indicates a wear-out dominated failure pattern typical of rotating machinery degradation. An age-replacement cost model is then formulated to minimize expected cost rate (USD per FH) by trading planned preventive cost, unplanned corrective cost, and downtime penalties. The Mean Time to Failure (MTTF) is approximately 6514 FH. Cost optimization results suggest an optimal preventive replacement interval in the range of 4750-6650 FH, with a baseline recommendation of approximately 5450 FH. A sensitivity analysis across representative cost scenarios demonstrates how the optimal preventive maintenance interval shifts when operational disruption costs increase. The proposed workflow provides a practically implementable template for maintenance planning of removal-driven line replaceable units under high utilization.
Reliability-Based Reassessment of Starter-Generator Preventive Maintenance Intervals on ATR 72-212A Aircraft Using Operational Removal Data Yoga Yulasmana; Bobi Gumelar Raspati
Journal of Ocean, Mechanical and Aerospace -science and engineering- Vol 70 No 2 (2026): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Publisher : International Society of Ocean, Mechanical and Aerospace -scientists and engineers- (ISOMAse)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36842/jomase.v70i2.631

Abstract

This paper re-assesses the preventive maintenance interval of starter-generator part number 8260-124 installed on ATR 72-212A aircraft using operational removal data from Airline X between 2019 and 2024. A quantitative case-study approach was applied to 65 removal records, comprising 39 scheduled and 26 unscheduled removals. The analysis included failure-mode classification, Pareto analysis, statistical distribution fitting, Mean Time to Failure estimation, survival analysis, Component Removal Rate, and Mean Time Between Unscheduled Removal. Brush wear was identified as the dominant failure mode, accounting for 53.8% of unscheduled removals. The lognormal distribution provided the best fit to the Time Since Installation data, with an adjusted Anderson–Darling statistic of 0.746 and a correlation coefficient of 0.989. The estimated MTTF was 907.022 flight hours, substantially below the existing 1,200-flight-hour maintenance interval, while the survival probability declined to 51.6% at 900 flight hours and 13.1% at 1,000 flight hours. These findings indicate that the current interval provides insufficient preventive margin. Therefore, an 800-flight-hour interval is recommended to reduce brush-related deterioration, unscheduled removals, and associated operational disruptions.
Co-Authors Beni Barliansah Bobi Gumelar Raspati