Optimization of maintenance strategies for railway track-bed considering probabilistic degradation models and different reliability levels
| Autor: | Massimo Losa, Sara Bressi, João Santos |
|---|---|
| Přispěvatelé: | Construction Management and Engineering |
| Rok vydání: | 2021 |
| Předmět: |
021110 strategic
defence & security studies Decision support system Railway line 021103 operations research Present value Maintenance Computer science Railway Markov chain UT-Hybrid-D 0211 other engineering and technologies Probabilistic logic Scheduling (production processes) 02 engineering and technology Industrial and Manufacturing Engineering Reliability engineering Multi-objective optimization Genetic algorithm Track management system Quality level Safety Risk Reliability and Quality |
| Zdroj: | Reliability engineering & system safety, 207:107359. Elsevier |
| ISSN: | 0951-8320 |
| Popis: | An optimization-based maintenance scheduling framework is an essential tool to plan the necessary investment to maintain the required performance of a railway line. In the present study, a methodology is proposed to minimize the present value of the life cycle maintenance costs and maximize the life cycle quality level of the track-bed considering different levels of reliability. Probabilistic degradation models are developed for predicting the evolution of the railway track condition over time. Afterwards, a Genetic Algorithm based optimization procedure is applied for obtaining a set of optimal solutions taking into account several constrains. The proposed methodology is applied to an Italian railway track-line case study. The results show that it is possible to develop a decision support system to help railway managers to schedule railway track maintenance operations based on the optimal trade-off between maintenance costs and railway track geometry condition for different levels of reliability. |
| Databáze: | OpenAIRE |
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