A risk-based modelling approach to maintenance optimization of railway rolling stock

2019 ◽  
Vol 25 (2) ◽  
pp. 272-293
Author(s):  
Fateme Dinmohammadi

Purpose Railway transport maintenance plays an important role in delivering safe, reliable and competitive transport services. An appropriate maintenance strategy not only reduces the assets’ lifecycle cost, but also will ensure high standards of safety and comfort for rail passengers and workers. In recent years, the majority of studies have been focused on the application of risk-based tools and techniques to maintenance decision making of railway infrastructure assets (such as tracks, bridges, etc.). The purpose of this paper is to present a risk-based modeling approach for the inspection and maintenance optimization of railway rolling stock components. Design/methodology/approach All the “potential failure modes and root causes” related to rolling stock systems are identified from an extensive literature review followed by an expert’s panel assessment. The failure causes are categorized into six groups of electrical faults, structural damages, functional failures, degradation, human errors and natural (external) hazards. Stochastic models are then proposed to estimate the likelihood (probability) of occurrence of a failure in the rolling stock system. The consequences of failures are also modeled by an “inflated cost function” that involves safety-related costs, corrective maintenance and renewal (M&R) costs, the penalty charges due to train delays or service interruptions as well as the costs associated with loss of reputation (or loss of fares) in the case of trip cancellation. Lastly, a time-varying risk-cost function is formulated to determine the optimal frequency of preventive inspection and maintenance actions for rolling stock components. Findings For the purpose of clearly illustrating the proposed risk-based inspection and maintenance modeling methodology, a case study of the Class 380 train’s pantograph system from a Scottish train operating company is provided. The results indicate that the proposed model has a substantial potential to reduce the M&R costs while ensuring a higher level of safety and service quality compared to the currently used inspection methodologies. Practical implications The railway rolling stocks should be regularly inspected and maintained so as to ensure network availability and reliability, passenger safety and comfort, and operations efficiency. Despite the best efforts of the maintenance staff, it is reported that a considerable amount of maintenance resources (e.g. budget, time, manpower) is wasted due to insufficiency or inefficiency of current periodic M&R interventions. The model presented in this paper helps the maintenance engineers to assess the current maintenance practices and propose or initiate improvement actions when needed. Originality/value There are few studies investigating the application of risk-based tools and techniques to inspection and maintenance decision making of railway rolling stock components. This paper presents a modeling approach aimed at planning the preventive repair and maintenance interventions for rolling stock components based on risk measures. The author’s model is also capable of incorporating real measurement information gathered at each inspection epoch to update future inspection plans.

2020 ◽  
Vol 6 (3) ◽  
pp. 76-87
Author(s):  
Elena S. Palkina

Background: At present, there is an urgent problem of renovation of rolling stock characterized by a high degree in Russia. The leading position in the country's transport system belongs to railway transport. In the context of declining demand for transportation investments in railcars, which represent a significant amount of capital investment, require reasonable management decisions. Aim: is to work out a decision-making model for renewal the transport organization's railway rolling stock. Methods: of technical, economic, investment and financial analysis, decision tree, graphical modeling, system approach. Results: The basic components of the decision-making model are determined. The key indicators of railway rolling stock renewal are defined, reflecting the criteria for making managerial decisions in the field of operational, investment and financial activities. A graphical model is proposed that interprets the decision support system for purchasing new railcars. Conclusion: Using the proposed model of decision-making in the field of renovation of rolling stock allows to transfer this process to a qualitatively new level, based on the results of an objective assessment of the current and forecast state of the management object according to various alternative scenarios and based on the selection of the rational decision by comparing the expected results for each of the considered alternatives and analysis degree of their compliance with the determined goals due to its versatility and complexity.


2019 ◽  
Vol 25 (1) ◽  
pp. 41-53 ◽  
Author(s):  
Dananjaya Wijesinghe ◽  
Harshini Mallawarachchi

Purpose The purpose of this paper is to determine the maintenance performance indicators (MPIs) which are significant for maintenance decision making in the apparel industry through an accurate maintenance performance measurement. Design/methodology/approach A quantitative research approach was followed. A questionnaire survey was used to collect the data which were evaluated based on Mean Weighted Rating and Relative Importance Index. Findings In total, 15 significant MPIs were determined which can directly affect maintenance decision making. A systematic approach was finally developed by allocating weightages for each critical MPI. Practical implications These results can be used to assist the decision-making process and as a performance measurement platform for maintenance management of the apparel industry. Originality/value The significance of maintenance has not been recognized and the value created through such massive efforts has remained hidden. Therefore, the need of adopting a performance-based approach for maintenance management in apparel industry exists. This research was aimed to provide a systematic approach to make decisions on maintenance management in the apparel industry in Sri Lanka.


2016 ◽  
Vol 22 (3) ◽  
pp. 218-237 ◽  
Author(s):  
Mohammad Sheikhalishahi ◽  
Liliane Pintelon ◽  
Ali Azadeh

Purpose – The purpose of this paper is to review current literature analyzing human factors in maintenance, and areas in need of further research are suggested. Design/methodology/approach – The review applies a novel framework for systematically categorizing human factors in maintenance into three major categories: human error/reliability calculation, workplace design/macro-ergonomics and human resource management. The framework further incorporates two well-known human factor frameworks, i.e., the Swiss Cheese model and the ergonomic domains framework. Findings – Human factors in maintenance is a pressing problem. The framework yields important insights regarding the influence of human factors in maintenance decision making. By incorporating various approaches, a robust framework for analyzing human factors in maintenance is derived. Originality/value – The framework assists decision makers and maintenance practitioners to evaluate the influence of human factors from different perspectives, e.g. human error, macro-ergonomics, work planning and human performance. Moreover, the review addresses an important subject in maintenance decision making more so in view of few human error reviews in maintenance literature.


2014 ◽  
Vol 21 (6) ◽  
pp. 1120-1144 ◽  
Author(s):  
He-Boong Kwon

Purpose – The purpose of this paper is to investigate the feasibility of using artificial neural networks (ANNs) in conjunction with data envelopment analysis (DEA) for the performance measurement of major mobile phone providers, and for subsequent predictions related to best performance benchmarking and decision making. Design/methodology/approach – DEA and ANN are combined, providing an integrated modeling approach via a two-stage process. DEA is used for front end measurement, while ANN provides learning and prediction capabilities. DEA analysis of industry characteristics is based on the measurement of each decision-making unit's (DMU) performance. Back propagation neural networks (BPNN) can then predict each DMU's efficiency score, based on the results of the DEA models. Additional BPNN models provide best performance predictions. Findings – The DEA module successfully evaluates the competitive status of firms in the mobile phone industry in terms of efficiency. Efficiency trends over the observation period reveal the dynamic nature of competition in this industry. The predictive power of the BPNN module has been demonstrated as well. The proposed system is an effective benchmarking and decision support tool, via its capability to simulate performance scenarios, thereby facilitating insightful, prudent decision making. Originality/value – This paper proposes the use of two different but complementary methods, DEA and ANN, in a combined performance modeling approach, and examines mobile phone providers. This methodology can improve users’ performance benchmarking and decision-making processes. Additionally, adaptive prediction capability is provided through approximating efficient frontiers, in addition to performance measurement.


2005 ◽  
Vol 297-300 ◽  
pp. 2687-2692
Author(s):  
Song Chun Choi ◽  
Sang In Han ◽  
Hee Jun Jung ◽  
Ji Yoon Kim

Recently, regulatory bodies quite often encourage to adopt risk-based inspection (RBI) and management programs because they can enhance safety simultaneously with deregulation in Korea. RBI is an integrated methodology that factors risk into inspection and maintenance decision making. This paper describes an example of how to use known risk assessment codes (API 580, API 581 BRD) to address such safety analysis requirements for risk management in the refining industry. Specifically, this paper reports the methodology and the results of application to the refinery units using the KGS-RBITM program, developed by the Korea Gas Safety Corporation in reference of API Codes and ASME PC (Post Construction) with a suitable consideration of Korean situation. The results of the risk and reliability assessment using KGS-RBITM program are useful in determining whether the detected defects are tolerable or required to be repaired. The subsequent decisions are to manage the future inspection, repair and maintenance planning in the risk reduction control.


2016 ◽  
Vol 23 (7) ◽  
pp. 1818-1833 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
S.S. Mahapatra

Purpose Robot selection is a critical decision-making task frequently experienced in almost every industries. It has become increasingly complex due to availability of large variety of robotic system in the present market with varying configuration, specification and flexibility. Improper selection may yield loss for the company in terms of potential profit as well as productivity. Hence, selection of an appropriate robot to suit a particular industrial application is definitely a challenging task. The paper aims to discuss these issues. Design/methodology/approach During robot selection, different criteria-attributes need to be taken under consideration. Criteria may be subjective or objective or a combination of both, depending on the situation. Criteria many be conflicting, in the sense that some criteria may require to be of higher value (higher-is-better), i.e. beneficial; while, others should correspond to lower values (lower-is-better), i.e. adverse or non-beneficial. Hence, the situation can be articulated as a multi-criteria decision-making problem. The specialty of Tomada de Decisión Inerativa Multicritero (TODIM) method is that it explores a global measurement of value calculable by the application of the paradigm of non-linear cumulative prospect theory. The method is based on a description, proved by empirical evidence, of how decision makers’ effectively make decisions in the face of risk. Findings Hence, the present work has aimed to explore the TODIM approach for industrial robot selection. Assuming all criteria have been quantitative in nature; the paper utilizes two different numeric data sets from available literature resource in perspectives of robot selection. Procedural hierarchy and application potential of the TODIM approach has been illustrated in detail in this reporting. Originality/value Variety of tools and techniques have already been documented in literature to solve different kinds of industrial decision-making problems; however, it seems that application of TODIM has got limited usage. Hence, application potential of TODIM has been demonstrated here in light of a robot selection problem.


Author(s):  
Song-Chun Choi ◽  
Sang-In Han ◽  
Hee J. Jung ◽  
Ji-Yoon Kim ◽  
Sung-Jin Song

Recently, regulatory bodies quite often encourage to adopt risk-based inspection (RBI) and management programs because they can enhance safety simultaneously with deregulation in Korea. RBI is an integrated methodology that factors risk into inspection and maintenance decision making. This paper describes an example of how to use known risk assessment codes (API 580, API 581 BRD) to address such safety analysis requirements for risk management in the refining industry. Specifically, this paper reports the methodology and the results of application to the refinery units using the KGS-RBI™ program, developed by the Korea Gas Safety Corporation in reference of API Codes and ASME PC (Post Construction) with a suitable consideration of Korean situation. The results of the risk and reliability assessment using KGS-RBI™ program are useful in determining whether the detected defects are tolerable or required to be repaired. The subsequent decisions are to manage the future inspection, repair and maintenance planning in the risk reduction control.


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