Szczegóły publikacji
Opis bibliograficzny
Reliability and life-cycle cost assessment of urban bus fleet maintenance strategies using Weibull analysis and multi-criteria decision analysis / Wasihun KENO, Janusz SZPYTKO // W: Transport Problems 2026 [Dokument elektroniczny] : XVIII International Scientific Conference : [Katowice - Łódź - Toruń, 24-26.06.2026] ; XIV International Symposium of Young Researchers : [Katowice, 22-23.06.2026]. — Wersja do Windows. — Dane tekstowe. — [Katowice : Silesian University of Technology. Faculty of Transport and Aviation Engineering], [2026]. — 1 dysk optyczny. — e-ISBN: 978-83-975865-2-9. — S. 717–727. — Wymagania systemowe: Adobe Reader ; napęd CD-ROM. — Bibliogr. s. 726–727, Abstr.
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 169181 |
|---|---|
| Data dodania do BaDAP | 2026-09-10 |
| Rok publikacji | 2026 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Politechnika Śląska |
Abstract
Urban bus fleet management involves coupled reliability and cost dynamics across heterogeneous subsystems. Failure processes vary by system, maintenance actions alter both subsequent failure behavior and vehicle downtime, and costs extend beyond workshop expenditure to service continuity and reserve fleet requirements. This study develops an integrated assessment framework combining Weibull-based modelling of inter-failure mileage, a maintenance-oriented life-cycle cost model, and a multi-criteria decision analysis procedure for ranking maintenance strategies. The approach is demonstrated using operational data from a municipal operator in Lublin, Poland, covering battery-electric and internal-combustion buses. Weibull parameters are used to characterize failure-intensity regimes, distinguish early-life and wear-driven behaviors, and determine reliability-based intervention thresholds. The cost model incorporates corrective and planned maintenance, repair-time structure, and downtime penalties. Strategy evaluation applies the analytic hierarchy process (AHP) weighting and compromise ranking method to compare run-to-failure, fixed-interval preventive maintenance, and condition-based maintenance. Results indicate that strategies reducing unplanned downtime and repair lead times achieve superior performance across most weighting scenarios. Fixed-interval maintenance remains sensitive to subsystem failure-intensity trends and may underperform when failure rates decline with mileage. Sensitivity analysis highlights decision risks associated with parameter uncertainty and heterogeneous, censored reliability data.
