Maintenance Decision Support Model for Railway Track Geometry Maintenance Planning Using Cost, Reliability, and Availability Factors: A Case Study

Kasraei, Ahmad; Zakeri, Jabbar Ali

doi:10.1177/03611981221077089

Cited by 9 publications

(4 citation statements)

References 44 publications

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“…The ndings of the study indicate that considering the interdependencies among intervention activities has a signi cant impact on the performance of the infrastructure and its LCC. Kasraei and Ali Zakeri, (2022) in their research, assessed estimated LCC associated with RAMS framework. They employed a stochastic linear degradation model, considering different thresholds to optimize the cost functions including inspection, PM and CM actions cost, and penalty for exceeding the speci c threshold.…”

Section: State Of the Artmentioning

confidence: 99%

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LCC-based approach for design and requirement specification for railway track system

Famurewa,

Kirilmaz,

Chamkhorami

et al. 2023

Preprint

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Life cycle cost (LCC) analysis is an important tool for effective infrastructure management. It is an essential decision support methodology for selection, design, development, construction, and maintenance of railway infrastructure system. Effective implementation of LCC analysis will assure cost-effective operation of railways from both investment and life-cycle perspectives. A major setback in the successful implementation of LCC by infrastructure managers is the availability of relevant, reliable, and structured data. Different cost estimation methods and prediction models have been developed to deal with this challenge. However, there is a need to integrate prediction models as an integral part of LCC methodology to account for possible changes in the model variables. This article presents an LCC based approach for requirement specification. It integrates degradation models with an LCC model to study the impact of change in design speed on key decision criteria such as track possession time, service life of track system, and LCC. The methodology is applied to an ongoing railway investment project in Sweden to investigate and quantify the impact of design speed change from 250 km/h to 320 km/h. The results from the studied degradation models show that the correction factor for a change in speed varies between 0,79 and 0,96. Using this correction factor to compensate for changes in design speed, the service life of ballasted track system is estimated to decrease by an average of 15%. Further, the LCC of the route under consideration will increase by an expected value of 30%.

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Section: State Of the Artmentioning

confidence: 99%

“…Degradation models [see references[2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] …”

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LCC-based approach for design and requirement specification for railway track system

Famurewa,

Kirilmaz,

Chamkhorami

et al. 2023

Preprint

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“…Additional researches can be found in Wu et al, 6 George-Williams and Patelli, 15 Verbert et al, 16 Chuang et al, 17 and Kasraei and Zakeri. 18 Most of the above studies for maintenance strategy are optimized to minimize maintenance cost or maximize system availability. Single-objective maintenance strategies are often applied only to equipment specified under particular conditions.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimal maintenance strategy considering imperfect preventive maintenance: A case study on railway VOBC

Cong

Shangguan

Cai

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part O:

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Preventive maintenance procedures for systems are designed to improve long-term operating performance and reduce maintenance costs. This paper attempts to seek a trade-off between system reliability and maintenance costs and explores the optimal multi-objective maintenance strategy applicable to different field situations. We first provide an overview of the problem and analyze the impacts of varying different maintenance activities on reliability. Then, a mathematical model of reliability losses and maintenance costs is defined and derived, which will be used to construct a multi-objective maintenance strategy. In this research, the PSO-SA stochastic optimization algorithm is proposed to discover the Pareto frontier to find the optimal preventive maintenance threshold and inspection interval that minimizes reliability loss and maintenance costs. Finally, a case study is performed with railway VOBC as an illustration. The analysis results illustrate that the proposed multi-objective maintenance strategy can satisfy the preferences of various decision-makers. It is suitable for different maintenance needs and can support the development of on-site maintenance strategies.

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“…Railways are one of the world's most essential means of transport, particularly in Iran. According to an analysis of Iran Railways' financial reports, one of the major issues in the rail transportation sector is the high cost of maintenance and repair (Kasraei and Ali Zakeri, 2022). The original investment in the railway is very significant, and it is expected to last a long time.…”

Section: Introductionmentioning

confidence: 99%

Development of an optimized maintenance scheduling for emergency rescue railway wagons using a genetic algorithm: a case study of Iran railways company

Zavareh

Fallahiarezoudar²,

Ahmadipourroudposht³

2022

IJQRM

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PurposeThis paper aims to optimize the maintenance scheduling of emergency rescue wagons in railway companies using a genetic algorithm (GA). It offers an integrated model for simultaneously solving maintenance planning, preventive maintenance, prognostic information and resource planning from which optimal levels of the system performance in terms of cost and repair time could be determined.Design/methodology/approachThis study initially evaluates the previous types of research in presenting the optimal model of the rescue train wagon for maintenance and repair planning and lists the identified criteria based on experts' opinions using fuzzy analytic hierarchy process (FAHP) and stepwise weight assessment ratio analysis (SWARA) techniques. Then, the final weight of the desired criteria is calculated. Later, the final decision matrix is evaluated by the experts. The final normal decision matrix is formed to select the optimal maintenance and repair planning plan based on the GA. Finally, two strategies including joint optimization strategy of preventive maintenance planning are compared with the independent preventive maintenance planning strategy.FindingsAccording to the primary results, three primary parameters, including technology, human damage caused by negligence and the average failure rate, should be considered for launching the GA model. Based on the results of the second part; by comparing the preventive maintenance planning strategy independently, the joint optimization strategy reduces the total cost of production up to 8.25%. Comparison results show that the total cost of joint optimization production is less than independent preventive maintenance and repair planning. Moreover, the value of total process time in joint optimization strategy was reduced by 1.2% compared to independent preventive maintenance (PM) planning (from 137.90 to 136.20 h).Originality/valueThe novelty of this paper lies on the application of the GAs to develop an optimized PM scheduling to localize the maintenance planning for maximizing productivity, avoid train accidents, reduce costs and increase efficiency and capacity.

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Maintenance Decision Support Model for Railway Track Geometry Maintenance Planning Using Cost, Reliability, and Availability Factors: A Case Study

Cited by 9 publications

References 44 publications

LCC-based approach for design and requirement specification for railway track system

LCC-based approach for design and requirement specification for railway track system

Multi-objective optimal maintenance strategy considering imperfect preventive maintenance: A case study on railway VOBC

Development of an optimized maintenance scheduling for emergency rescue railway wagons using a genetic algorithm: a case study of Iran railways company

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