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Lin J.,Lulea University of Technology | Lin J.,Lulea Railway Research Center
Journal of Quality and Reliability Engineering | Year: 2014

The recent proliferation of Markov chain Monte Carlo (MCMC) approaches has led to the use of the Bayesian inference in a wide variety of fields. To facilitate MCMC applications, this paper proposes an integrated procedure for Bayesian inference using MCMC methods, from a reliability perspective. The goal is to build a framework for related academic research and engineering applications to implement modern computational-based Bayesian approaches, especially for reliability inferences. The procedure developed here is a continuous improvement process with four stages (Plan, Do, Study, and Action) and 11 steps, including: (1) data preparation; (2) prior inspection and integration; (3) prior selection; (4) model selection; (5) posterior sampling; (6) MCMC convergence diagnostic; (7) Monte Carlo error diagnostic; (8) model improvement; (9) model comparison; (10) inference making; (11) data updating and inference improvement. The paper illustrates the proposed procedure using a case study. © 2014 Jing Lin.

Famurewa S.M.,Lulea University of Technology | Asplund M.,Lulea University of Technology | Galar D.,Lulea University of Technology | Kumar U.,Lulea University of Technology | Kumar U.,Lulea Railway Research Center
International Journal of Systems Assurance Engineering and Management | Year: 2013

The achievement of maintenance objectives to support the overall business objectives is the pursuit of any maintenance department. Using in-house or outsourced maintenance service provider is a decision which poses challenge in the management of maintenance function. Should the decision be for outsourcing, the next concern is the selection of the most appropriate strategy suitable for the business environment, structure and philosophy. In an effort to improve maintenance function so as to deliver set objectives, some infrastructure managers adopted the approach of outsourcing maintenance function, giving larger responsibilities to maintenance service providers called contractors. Moreover, such change requires adequate attention to meet the pressing need of achieving the designed capacity of the existing railway infrastructure and also support a competitive and sustainable transport system. This paper discusses performance based railway infrastructure maintenance contracting with its issues and challenges. The approach of this article is review of literature and as well as synthesis of practices. A framework to facilitate the successful implementation of performance based railway infrastructure maintenance is presented. Also a performance monitoring system is proposed to assess the outcome and identify improvement potentials of the maintenance outsourcing strategy. A case study is given to demonstrate the monitoring of a typical maintenance activity that can be outsourced using this outsourcing strategy. © 2013 The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

Khouy I.A.K.,Lulea University of Technology | Schunnesson H.,Lulea University of Technology | Nissen A.,Lulea Railway Research Center | Juntti U.J.,Lulea University of Technology
International Journal of COMADEM | Year: 2012

The measurement and improvement of track quality are key issues in determining both the time and cost of railway maintenance. Efficient track geometry maintenance ensures optimum allocation of limited maintenance resources and has an enormous effect on maintenance efficiency. Applying the appropriate tamping strategy also helps reduce maintenance costs, making operations more cost effective and leading to increased safety and passenger comfort. In this paper, track geometry data from the iron ore line in northern Sweden, which handles both passenger and freight trains, are used to calculate track quality degradation trend in a cold climate. The paper describes Trafik verket's (Swedish Transport Administration) tamping strategy and illustrates the distribution of safety failures in different seasons. It also analyses the track geometry degradation and discuss about the possible reasons for distribution of failures over a year and along the track. © 2012 COMADEM International.

Lin J.,Lulea University of Technology | Lin J.,Lulea Railway Research Center | Pulido J.,ReliaSoft Corporation | Asplund M.,Lulea University of Technology
Reliability Engineering and System Safety | Year: 2015

This paper undertakes a general reliability study using both classical and Bayesian semi-parametric degradation approaches. The goal is to illustrate how degradation data can be modelled and analysed to flexibly determine reliability to support preventive maintenance strategy making, based on a general data-driven framework. With the proposed classical approach, both accelerated life tests (ALT) and design of experiments (DOE) technology are used to determine how each critical factor affects the prediction of performance. With the Bayesian semi-parametric approach, a piecewise constant hazard regression model is used to establish the lifetime using degradation data. Gamma frailties are included to explore the influence of unobserved covariates within the same group. Ideally, results from the classical and Bayesian approaches will complement each other. To demonstrate these approaches, this paper considers a case study of locomotive wheel-set reliability. The degradation data are prepared by considering an Exponential and a Power degradation path separately. The results show that both classical and Bayesian semi-parametric approaches are useful tools to analyse degradation data and can, therefore, support a company in decision making for preventive maintenance. The approach can be applied to other technical problems (e.g. other industries, other components). © 2014 Elsevier Ltd. All rights reserved.

Famurewa S.M.,Lulea University of Technology | Famurewa S.M.,Lulea Railway Research Center | Juntti U.,Lulea Railway Research Center | Juntti U.,Performance in Cold AB | And 3 more authors.
Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit | Year: 2015

The demand for increased capacity on existing railway networks is a challenge for many Europe-based infrastructure managers; addressing this challenge requires augmented utilisation of track possession time. It is considered that large-scale maintenance tasks such as geometry maintenance can be improved; thus, reducing the on-track maintenance time and allowing more traffic. In this study, an analysis of track geometry maintenance was performed with the objective of reducing the required possession time. The procedure and models for planning and optimizing track geometry maintenance are presented. A statistical model that uses a simulation approach was used to determine the condition of the track geometry, and a schedule optimization problem was formulated to support intervention decisions and optimize the track possession time. The results of the case study show that optimizing the maintenance shift length and cycle length are opportunities to reduce the extent of track possession required for the maintenance of the track geometry. In addition, continuous improvement of the tamping process through lean analysis promises about a 45% reduction in the required possession time for a tamping cycle. © 2015 Institution of Mechanical Engineers.

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