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Статті в журналах з теми "Reliability, Human error, Railway, Maintenance"
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Rahimi, Masoumeh, Haochen Liu, Isidro Durazo Cardenas, Andrew Starr, Amanda Hall, and Robert Anderson. "A Review on Technologies for Localisation and Navigation in Autonomous Railway Maintenance Systems." Sensors 22, no. 11 (May 31, 2022): 4185. http://dx.doi.org/10.3390/s22114185.
Повний текст джерелаАнотація:
Smart maintenance is essential to achieving a safe and reliable railway, but traditional maintenance deployment is costly and heavily human-involved. Ineffective job execution or failure in preventive maintenance can lead to railway service disruption and unsafe operations. The deployment of robotic and autonomous systems was proposed to conduct these maintenance tasks with higher accuracy and reliability. In order for these systems to be capable of detecting rail flaws along millions of mileages they must register their location with higher accuracy. A prerequisite of an autonomous vehicle is its possessing a high degree of accuracy in terms of its positional awareness. This paper first reviews the importance and demands of preventive maintenance in railway networks and the related techniques. Furthermore, this paper investigates the strategies, techniques, architecture, and references used by different systems to resolve the location along the railway network. Additionally, this paper discusses the advantages and applicability of on-board-based and infrastructure-based sensing, respectively. Finally, this paper analyses the uncertainties which contribute to a vehicle’s position error and influence on positioning accuracy and reliability with corresponding technique solutions. This study therefore provides an overall direction for the development of further autonomous track-based system designs and methods to deal with the challenges faced in the railway network.
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Dinmohammadi, Fateme. "A risk-based modelling approach to maintenance optimization of railway rolling stock." Journal of Quality in Maintenance Engineering 25, no. 2 (May 7, 2019): 272–93. http://dx.doi.org/10.1108/jqme-11-2016-0070.
Повний текст джерелаАнотація:
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.
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Consilvio, A., M. Iorani, V. Iovane, M. Sciutto, and G. Sciutto. "Real-time monitoring of the longitudinal strain of Continuous Welded Rail for safety improvement." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 234, no. 10 (December 4, 2019): 1238–52. http://dx.doi.org/10.1177/0954409719890166.
Повний текст джерелаАнотація:
Continuous welded rail maintenance plays a significant role in ensuring high levels of rail traffic and safety. Temperature variations, excessive alignment defects, decreased fastening system resistance and train braking (always in the same stretches and in the same direction) may result in rail buckling or rail breaks. The current traditional monitoring systems and procedures for continuous welded rail consist of programmed discontinuous diagnostic surveys that require personnel intervention on site. Moreover, these traditional systems often imply destructive and invasive operations on the track that may lead to interruption of railway operations. This paper proposes a Rail Strain Monitoring System (RSMS) that performs a real-time rail strain monitoring and allows rail inspection without personnel on site. Using strain gauges and temperature sensors, placed on the rail in specific measurement points, the proposed Rail Strain Monitoring System performs a multi-parameter check by measuring, at the same time, the temperature, the rail strain and the neutral temperature of the rail. The paper describes the mode of operation of the Rail Strain Monitoring System, the calibration procedure and the results from the field, and highlights the advantages of this system in comparison to other traditional monitoring systems. The safety improvement that can be achieved with the application of the Rail Strain Monitoring System is analysed. In particular, the reliability of the system is evaluated and compared to the human error probability in the traditional manual inspections. Finally, the reduction of derailment risk and related economic damages is estimated.
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Ciszewski, Tomasz, Waldemar Nowakowski, and Zbigniew Łukasik. "A fault tree analysis-based method of railway traffic control systems safety assessment (Metoda oceny bezpieczeństwa systemów sterowania ruchem kolejowym z wykorzystaniem FTA)." WUT Journal of Transportation Engineering 128 (March 1, 2020): 49–57. http://dx.doi.org/10.5604/01.3001.0014.0902.
Повний текст джерелаАнотація:
Railway traffic control and signaling systems are safety-related, and thus it is crucial to provide them with an appropriate level of safety. Technological development has led to an increase in the functionality and reliability of these systems, taking into account the high safety requirements. Therefore, the operations involving the design, construction, and maintenance of railway traffic control and signaling systems should include a safety analysis. The safety analysis of railway traffic and signaling systems assumes that a primary event may cause a series of intermediate events, which then may lead to a disaster causing significant material losses and fatalities. Due to the random nature of the occurrences of the adverse events (failures, human errors), the probabilistic methods are often used to estimate risk. One of the risk assessment methods is Fault Tree Analysis (FTA). The authors of the paper conducted a qualitative safety analysis of level crossing protection systems using the FTA method. The requirements for the level crossing protection system were described, which we then used to write out FTA diagrams. The specific technical and quality requirements for railway traffic control and signaling systems result from the need to ensure a high safety level. Risk assessment is a required step in the evaluation of the safety and reliability of these systems. The authors of the paper applied the FTA method to the safety assessment of the level crossing protection system. The obtained results should be helpful in the process of design new railway traffic control and signaling systems. Systemy sterowania ruchem kolejowym są systemami związanymi z bezpieczeństwem, a tym samym bardzo ważnym aspektem jest dążenie do zapewnienia przez nie odpowiednie-go poziomu bezpieczeństwa. Wraz z rozwojem technologicznym następował wzrost funkcjonalności i niezawodności tych systemów, przy uwzględnieniu wysokich wymagań w odniesieniu do bezpieczeństwa. Dlatego też, działania polegające na projektowaniu, konstruowaniu i utrzymaniu systemów sterowania ruchem kolejowym powinny uwzględniać analizę bezpieczeństwa. W takiej analizie zakłada się, że zdarzenie pierwotne może wywołać ciąg zdarzeń wtórnych, które następnie mogą doprowadzić do katastrofy, niosącej ze sobą duże straty materialne i śmierć ludzi. Ze względu na losowy charakter występowania zdarzeń niepożądanych (uszkodzenie, błąd ludzki), często przy szacowaniu ryzyka wykorzystuje się w opis probabilistyczny. Jedną z metod szacowania ryzyka jest metoda FTA (Fault Tree Analysis). Autorzy artykuły przy wykorzystaniu metody FTA przeprowadzili analizę jakościową bezpieczeństwa przejazdów kolejowych wyposażonych w systemy zabezpieczenia. Opisano wymagania dla systemu zabezpieczenia przejazdu, które następnie posłużyły do zbudowania drzew FTA. Specyficzne wymagania techniczne i jakościowe dla systemów sterowania ruchem kolejowym wynikają z konieczności zapewnienia wysokiego poziomu bezpieczeństwa. W celu oceny bezpieczeństwa i niezawodności tych systemów, musimy podejmować działania w zakresie oceny ryzyka. Autorzy publikacji zastosowali metodę FTA do oceny bezpieczeństwa systemu zabezpieczenia przejazdu. Uzyskane wyniki mogą być pomocne w procesie konstruowania nowych systemów sterowania ruchem kolejowym. null
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Janota, Aleš, Rastislav Pirník, Juraj Ždánsky, and Peter Nagy. "Human Factor Analysis of the Railway Traffic Operators." Machines 10, no. 9 (September 19, 2022): 820. http://dx.doi.org/10.3390/machines10090820.
Повний текст джерелаАнотація:
The human factor is an essential aspect of the operability and safety of many technical systems. This paper focuses on the analysis of human errors in the railway domain. The subject of human reliability analysis is the behavior of operators of station-signaling systems responsible for rail traffic management. We use a technique for human-error rate prediction as the 1st generation human reliability analysis to deal with task analyses, error identification and representation, and the quantification of human error probabilities. The paper contributes to the comparison of three technologically different railway traffic control systems, having different degrees of automation—from the manually operated (electro-mechanical), through semi-automated (relay-based) to almost fully automated (computer-based) station-signaling systems. We observe the frequency of individual operations performed in time intervals and calculate human error probability and human success probability values for each operation. Thus, we can analyze human reliability and compare the workload of operators working with control systems of different degrees of automation.
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Manuilov, N. I. "HUMAN FACTOR INFLUENCE ON TRAIN BRAKE EQUIPMENT RELIABILITY." World of Transport and Transportation 15, no. 3 (June 28, 2017): 196–204. http://dx.doi.org/10.30932/1992-3252-2017-15-3-19.
Повний текст джерелаАнотація:
[For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version)].ABSTRACT The article considers the human factor influence on trouble-free operation of brake equipment of trains. The study was carried out by an analytical method, based on the statistics of equipment failures, assessment of implementation of the current rules for railway rolling stock maintenance. The problem of the lack of an effective device for diagnosing the brake network of a train, which would provide control over its integrity and density in the course of traffic and during stops, is revealed. At the same time, it is also necessary to reduce time for measuring density of the brake network, the train to automate this process. Keywords: railway, traffic safety, braking equipment, train brake network density, reliability, human factor.
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Franciosi, Chiara, Valentina Di Pasquale, Raffaele Iannone, and Salvatore Miranda. "A taxonomy of performance shaping factors for human reliability analysis in industrial maintenance." Journal of Industrial Engineering and Management 12, no. 1 (February 20, 2019): 115. http://dx.doi.org/10.3926/jiem.2702.
Повний текст джерелаАнотація:
Purpose: Human factors play an inevitable role in maintenance activities, and the occurrence of Human Errors (HEs) affects system reliability and safety, equipment performance and economic results. The high HE rate increased researchers’ attention towards Human Reliability Analysis (HRA) and HE assessment approaches. In these approaches, various environmental and individual factors influence the performance of maintenance operators affecting Human Error Probability (HEP) with a consequent variability in the success of intervention. However, a deep analysis of such factors in the maintenance field, often called Performance Shaping Factors (PSFs), is still missing. This has led the authors to systematically evaluate the literature on Human Error in Maintenance (HEM) and on the PSFs, in order to provide a shared PSF taxonomy.Design/methodology/approach: A Systematic Literature Review (SLR) was conducted to identify and select peer-reviewed papers that provided evidence on the relationship between maintenance activities and human performance. The obtained results provided a wide overview in the field of interest, shedding light on three main research areas of investigation: methodologies for human error analysis in maintenance, performance shaping factors and maintenance error consequences. In particular, papers belonging to the area of PSFs were analysed in-depth in order to identify and classify the PSFs, with the aim of achieving the PSF taxonomy for maintenance activities. The effects of each PSF on human reliability were defined and detailed.Findings: A total of 63 studies were selected and then analysed through a systematic methodology. 46% of these studies presented a qualitative/quantitative assessment of PSFs through application in different maintenance activities. Starting from the findings of the aforementioned papers, a PSF taxonomy specific for maintenance activities was proposed. This taxonomy represents an important contribution for researchers and practitioners towards the improvement of HRA methods and their applications in industrial maintenance.Originality/value: The analysis outlines the relevance of considering HEM because different error types occur during the maintenance process with non-negligible effects on the system. Despite a growing interest in HE assessment in maintenance, a deep analysis of PSFs in this field and a shared PSF taxonomy are missing. This paper fills the gap in the literature with the creation of a PSF taxonomy in industrial maintenance. The proposed taxonomy is a valuable contribution for growing the awareness of researchers and practitioners about factors influencing maintainers’ performance.
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Wulandari, Aditya Praswuri. "ANALISIS HUMAN RELIABILITY PADA OPERATOR MAINTENANCE MESIN UNTUK MENGENDALIKAN HUMAN ERROR DENGAN METODE SPAR-H DI PT. TJOKRO PUTRA PERKASA." Indonesian Journal of Occupational Safety and Health 6, no. 3 (October 30, 2018): 269. http://dx.doi.org/10.20473/ijosh.v6i3.2017.269-277.
Повний текст джерелаАнотація:
Operator have considerable contribution in the operation of the system trough its role in the completion of their work. Therefore it is important to know the operator’s reliability (human reliability). The levels of human reliability is determined by calculating the potential in making mistakes, known as human error. Human error is influenced by the inadequate system design, the working bad situation, the high complexity of the work, the characteristics of human behaviour, the mental and physical fatigue, the working environment and organizational policies. The main objective of this study was to analyze the reliability of the human operators to control the occurance of human error. This study was an observational with cross-sectional approach. The study was conducted on 14 of operators maintenance machine in PT. Tjokro Putraperkasa. Data were collected by means of interview and observation. Data were obtained using Hierarchical Task Analysis (HTA) and Standardized Plant Analysis Risk Human Reliability Assessment (SPAR-H). The result showed that most (80%) of the operators did not wear Personal Protective Equipment (PPE), possible were widely found in preventive maintenance machine bubut, the high score (HEP= 0,0477) of human unreliability was found in operators working intruction in machine bubut, hobbing and CNC, as whole the system reliability was still low, and the majority (80%) of operators were still unreliable in doing their job.Keywords:human error, human reliability, SPAR-H.
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Sheikhalishahi, Mohammad, Liliane Pintelon, and Ali Azadeh. "Human factors in maintenance: a review." Journal of Quality in Maintenance Engineering 22, no. 3 (August 8, 2016): 218–37. http://dx.doi.org/10.1108/jqme-12-2015-0064.
Повний текст джерелаАнотація:
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.
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Huang, Chao-Hui, Chun-Ho Wang, and Guan-Liang Chen. "Multiobjective Multistate System Preventive Maintenance Model with Human Reliability." International Journal of Aerospace Engineering 2021 (July 14, 2021): 1–16. http://dx.doi.org/10.1155/2021/6623810.
Повний текст джерелаАнотація:
Modern equipment is designed to operate under deteriorating performance conditions resulting from internal ageing and/or external environmental impacts influencing downstream maintenance. This study focuses on the development of a multistate system (MSS) that considers a human reliability factor associated with maintenance personnel—a condition-based multiobjective MSS preventive maintenance model (MSSPMM). The study assumes that no more than one maintenance activity is performed to achieve the most appropriate preventive maintenance (PM) strategy and easy implementation and to reduce maintenance error due to human reliability. The MSS performance based on mean system unavailability and total maintenance cost is evaluated using a stochastic model approach, and then, the MSSPMM is used for optimisation. A customised version of the nondominated sorting genetic algorithm III is employed to ensure efficient solution of the PM model with human reliability—which is considered a constrained multiobjective combinatorial optimisation problem. The optimised solutions are determined from the nondominated Pareto frontier comprising the diversified PM alternatives. A helicopter power transmission system is used as an example to illustrate the efficacy and applicability of the proposed approach through sensitivity analyses with relevant parameters.
Дисертації з теми "Reliability, Human error, Railway, Maintenance"
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Abu, Hawwach Mohammed. "Human errors in industrial operations and maintenance." Thesis, Mälardalens högskola, Innovation och produktrealisering, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54794.
Повний текст джерелаАнотація:
Within maintenance activities and industrial operations, human is subjected to different kind of stresses and situation that could result in mistakes and accidents. The human errors in maintenance and manufacturing are an unexplored latter such that a little focusis invested in this area. The report aims to widen up the understanding of the human error in maintenance and manufacturing area. Aviation and marine operations are the most sectors that are subjected to human errors according tothe literature. There aredifferent types of human error that have effect on quality and overall effectivity. Human reliability models are one method to quantify human errors and usually used for the identification of human errors and HEP calculation. The most common reliability measurement methods are HEART, THERP and SLIM which are used depending on application and industry. As a part of efforts to define differences between those reliability models, literature including different industries is used and itis found that expert judgement influences the success and accuracy of such methods. There are many causes for human errors depending on the application but, communication and procedures followed are the most contributing factors. There is always a probability of existence of human errors as the mistake done by workers are inevitable. Industry 4.0 can help in decreasing human errors through the introduction of operator 4.0 as well as other approaches like training and upgrading organizational standards.
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Rangra, Subeer. "Performance shaping factor based human reliability assessment using valuation-based systems : application to railway operations." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2375/document.
Повний текст джерелаАнотація:
L'homme reste l'un des éléments essentiels des opérations de transport modernes. Les méthodes d'analyse de la fiabilité humaine (HRA) fournissent une approche multidisciplinaire pour évaluer l'interaction entre les humains et le système. Cette thèse propose une nouvelle méthodologie HRA appelée PRELUDE (Performance shaping factor based human REliability assessment using vaLUation-baseD systems). Les facteurs de performance sont utilisés pour caractériser un contexte opérationnel dangereux. Le cadre de la théorie des fonctions de croyance et des systèmes d'évaluation (VBS) utilise des règles mathématiques pour formaliser l'utilisation de données d'experts et la construction d'un modèle de fiabilité humaine, il est capable de représenter toutes sortes d'incertitudes. Pour prédire la probabilité d'erreur humaine dans un contexte donné, et de fournir une remontée formelle pour réduire cette probabilité. La deuxième partie de ce travail démontre la faisabilité de PRELUDE avec des données empiriques. Un protocole pour obtenir des données à partir de simulateurs, et une méthode de transformation et d'analyse des données sont présentés. Une campagne expérimentale sur simulateur est menée pour illustrer la proposition. Ainsi, PRELUDE est en mesure d'intégrer des données provenant de sources (empiriques et expertes) et de types (objectifs et subjectifs) différents. Cette thèse aborde donc le problème de l'analyse des erreurs humaines, en tenant compte de l'évolution du domaine des méthodes HRA. Elle garde la facilité d'utilisation de l'industrie ferroviaire, fournissant des résultats qui peuvent facilement être intégrés avec les analyses de risques traditionnelles. Dans un monde de plus en plus complexe et exigeant, PRELUDE fournira aux opérateurs ferroviaires et aux autorités réglementaires une méthode permettant de s'assurer que le risque lié à l'interaction humaine est compris et géré de manière appropriée dans son contexteHumans are and remain one of the critical constituents of modern transport operations. Human Reliability Analysis (HRA) methods provide a multi-disciplinary approach: systems engineering and cognitive science methods to evaluate the interaction between humans and the system. This thesis proposes a novel HRA methodology acronymed PRELUDE (Performance shaping factor based human REliability assessment using vaLUation-baseD systEms). Performance shaping factors (PSFs) are used to characterize a dangerous operational context. The proposed framework of Valuation-based System (VBS) and belief functions theory (BFT) uses mathematical rules to formalize the use of expert data and construction of a human reliability model capable of representing all kinds of uncertainty. PRELUDE is able to predict the human error probability given a context, and also provide a formal feedback to reduce the said probability. The second part of this work demonstrates the feasibility of PRELUDE with empirical data from simulators. A protocol to obtain data, a transformation and data analysis method is presented. An experimental simulator campaign is carried out to illustrate the proposition. Thus, PRELUDE is able to integrate data from multiple sources (empirical and expert) and types (objective and subjective). This thesis, hence address the problem of human error analysis, taking into account the evolution of the HRA domain over the years by proposing a novel HRA methodology. It also keeps the rail industry’s usability in mind, providing a quantitative results which can easily be integrated with traditional risk analyses. In an increasingly complex and demanding world, PRELUDE will provide rail operators and regulatory authorities a method to ensure human interaction-related risk is understood and managed appropriately in its context
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Mattmuller, Adam. "Nuclear Power Plant Maintenance Improvement via Implementation of Wearable Technology." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461760209.
Повний текст джерела
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Guidi, Giulia. "The importance of human factor and maintenance activities in risk assessment for railway applications." Doctoral thesis, 2022. http://hdl.handle.net/2158/1264674.
Повний текст джерелаАнотація:
This thesis focuses on the importance of human factor and maintenance activities in risk assessment for railway applications.
Risk based maintenance is a key factor of RAMS (Reliability, Availability, Maintainability and Safety) for railway. One of the widest used techniques to evaluate the optimal maintenance policy of complex systems is the RCM (Reliability Centred Maintenance). This procedure starts from a failure analysis before individuating the optimal maintenance operation focusing on a decision diagram which is very vague and subjective. Trying to solve this problem, the first part of this work introduces an innovative approach that proposes a new decision-making diagram. The new diagram is based on a fuzzy-FMECA (Failure Modes, Effects and Criticality Analysis) assessment combined with some Boolean variables in order to provide a unique maintenance task for every identified scenario depending on the O (Occurrence), S (Severity) and D (Detection) assessment. The proposed procedure provides a diagnostic-oriented decision diagram able to solve the problems of the standardized RCM procedure and, at the same time, to optimize the Operation&Maintenance cost and the system availability favoring CBM (Condition-Based Maintenance) tasks such as Condition Monitoring and Failure Finding procedures.
The proposed enhanced RCM is based on a FMECA, which is a central technique used to perform risk assessment in every industrial and technological field. Despite this, several papers in literature agree that classical FMECA suffer many drawbacks. The developed fuzzy FMECA technique aims to solve all these problems with a simple and effective tool that could be applied in railway applications. Moreover, an innovative risk threshold estimation method has been developed to divide critical and negligible modes after the FMECA assessment in order to prioritize countermeasures.
The second topic covered by this research is the analysis of human reliability in railway engineering. Human factors remarkably contribute to railway accidents and, as a matter of fact, it is one of the main causes of accident on the last years. This is the reason why it is mandatory to study and evaluate human reliability in maintenance operation of railway systems. Literature is plenty of techniques developed to study the human reliability, however the only validated method for railway field is RARA (Railway Action Reliability Assessment). RARA has been developed in 2012 and is characterized by a highly subjective and complex assessment. Trying to solve these needs, this work proposes an improvement of RARA method able to solve its main shortcomings thanks to fuzzy logic. Using the proposed fuzzy-RARA the analyst is facilitated in the assessment of the numerical parameters and the subjectivity is remarkably mitigated.
Finally, the last part of the work presents an innovative technique specifically developed for railway. This method integrates the Weibull distribution and aims to provide a time-dependent model for the Human Error Probability. Furthermore, the proposed method gave the possibility to select one or more variable breaks within the work shift, which is an aspect generally neglected by the state-of-the art.
Both the proposed methods for Human Reliability Analysis have been tested on the maintenance activities performed by qualified operators nearby the railroad. The results highlight the significant contributions of the human error within the contexts of the complete risk assessment of the railway system.
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Islam, TMR. "Human reliability assessments for the maintenance operation of marine systems." Thesis, 2017. https://eprints.utas.edu.au/23790/7/Islam_whole_thesis_ex_pub_mat.pdf.
Повний текст джерелаАнотація:
Human intervention plays a critical role in the maintenance operations of marine systems. Consequently human factors are identified as one of the main causes of accidents in marine systems especially during maintenance operations. Characterisation and assessments of human factors in the form of Human Reliability Assessment (HRA) is an important step to better understand accident causation during maintenance operations. This would help minimize human errors and enhance overall safety and reliability of the marine systems. The International Maritime Organization (IMO) recommends implementing HRA to quantitatively assess the effect of human errors as a part of quantitative risk analysis of shipping operations. However, HRA for the maintenance operations of marine systems is not given due attention. This PhD research is focused on developing novel methodologies to accurately estimate the Human Error Probability (HEP) during the maintenance operations of marine systems. The developed methodologies will help in better understanding accident causation, estimation of HEPs, and to develop the required strategies to minimize the HEP.
This thesis contains seven chapters. The first chapter provides the introduction and general structure of the thesis. Second chapter presents development of a novel methodology to assess the HEP for the maintenance operation of marine systems. The developed methodology is applied to the maintenance procedures of a marine engine as a case study. The results showed that among the 43 considered activities, ‘inspection and overhaul of piston/piston rings’ have the lowest HEP meaning it has a low consequence for accidents. On the other hand, ‘fuel and lubricating oil filters pressure difference checking’ and ‘renew filter element’s activity have the highest HEP indicating it has highest chances of accidents. The third chapter presents a novel monograph as an easy-to-use tool to estimate HEP for marine operations. The developed monograph is applied to the maintenance procedures of a High Pressure (HP) fuel pump for estimating HEP. The results showed that ‘inspection of fuel injectors’, ‘renewing nozzles’ and ‘testing’ has the highest HEP. While the fourth chapter proposes a novel technique by revising and modifying the Human Error Assessment and Reduction Technique (HEART) to assess the HEP during the maintenance activities in marine operations. The developed methodology is applied to the maintenance procedures of a marine engine exhaust turbocharger as a case study. Application of the developed methodology confirms that extreme weather condition, extreme workplace temperature, high ship motion, high level of noise and vibration, and work overload and stress all increase the likelihood of human error as well as likelihood of potential accidents. The fifth chapter presents development of an HEP assessment technique using an advanced probabilistic technique named Bayesian Network (BN). The developed methodology is tested on the maintenance of marine engine’s cooling water pump for engine department and anchor windlass for deck department. The case study results showed that category “A” chief engineer/captain (highest rank) with 10 years or more experience and voyage duration of 1 month has the lowest HEP, and category “D” fourth engineer/third officer with 5 years’ experience and voyage duration of 4 months has the highest HEPs. As part of the HRA, extensive data collection activity was conducted. The details of this activity and outcome are reported in this thesis. The collected data is analysed for normality and also pair-wise significance test and presented in chapter 6. It helps to study generalization of the data and also to identify the relative importance of the factors. Workload and stress, and ship motion (roll and pitch) are identified to be critical factors affecting human performance on on-board maintenance operations. The collected data played an important role in testing and verifying earlier developed techniques and models. Chapter 7 includes the conclusions of the thesis.
This thesis aims to serve as a comprehensive source of knowledge and technique to form a better understanding of human factors associated with maintenance activities in marine operations. It will assist in ensuring implementation of IMO requirement for safe and reliable maintenance activities and marine operations.
Книги з теми "Reliability, Human error, Railway, Maintenance"
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S, Dhillon B. Human reliability, error, and human factors in power generation. Cham: Springer, 2014.
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Human reliability, error, and human factors in engineering maintenance: With reference to aviation and power generation. Boca Raton: Taylor & Francis, 2009.
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Schneider, Jörg, and Ton Vrouwenvelder. Introduction to safety and reliability of structures. 3rd ed. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 1997. http://dx.doi.org/10.2749/sed005.
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<p>Society expects that buildings and other structures are safe for the people who use them or who are near them. The failure of a building or structure is expected to be an extremely rare event. Thus, society implicitly relies on the expertise of the professionals involved in the planning, design, construction, operation and maintenance of the structures it uses.<p>Structural engineers devote all their effort to meeting society’s expectations effi ciently. Engineers and scientists work together to develop solutions to structural problems. Given that nothing is absolutely and eternally safe, the goal is to attain an acceptably small probability of failure for a structure, a facility, or a situation. Reliability analysis is part of the science and practice of engineering today, not only with respect to the safety of structures, but also for questions of serviceability and other requirements of technical systems that might be impacted by some probability.<p>The present volume takes a rather broad approach to safety and reliability in Structural Engineering. It treats the underlying concepts of safety, reliability and risk and introduces the reader in a fi rst chapter to the main concepts and strategies for dealing with hazards. The next chapter is devoted to the processing of data into information that is relevant for applying reliability theory. Two following chapters deal with the modelling of structures and with methods of reliability analysis. Another chapter focuses on problems related to establishing target reliabilities, assessing existing structures, and on effective strategies against human error. The last chapter presents an outlook to more advanced applications. The Appendix supports the application of the methods proposed and refers readers to a number of related computer programs.<p>This book is aimed at both students and practicing engineers. It presents the concepts and procedures of reliability analysis in a straightforward, understandable way, making use of simple examples, rather than extended theoretical discussion. It is hoped that this approach serves to advance the application of safety and reliability analysis in engineering practice.<p>The book is amended with a free access to an educational version of a Variables Processor computer program. FreeVaP can be downloaded free of charge and supports the understanding of the subjects treated in this book.
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Dhillon, B. S. Human Reliability, Error, and Human Factors in Engineering Maintenance. CRC Press, 2009. http://dx.doi.org/10.1201/9781439803844.
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Dhillon, B. S. Human Reliability, Error, and Human Factors in Engineering Maintenance: With Reference to Aviation and Power Generation. Taylor & Francis Group, 2009.
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Dhillon, B. S. Human Reliability, Error, and Human Factors in Engineering Maintenance: With Reference to Aviation and Power Generation. Taylor & Francis Group, 2009.
Знайти повний текст джерелаЧастини книг з теми "Reliability, Human error, Railway, Maintenance"
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Dhillon, B. S. "Human Error in Power Plant Maintenance." In Springer Series in Reliability Engineering, 135–49. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04019-6_10.
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Dhillon, B. S. "Human Reliability and Error in Maintenance." In Handbook of Maintenance Management and Engineering, 695–710. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-472-0_25.
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Hunter, Josh, and John McDermid. "Investigating Human Error Within GoA-2 Metro Lines." In Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification, 179–91. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05814-1_13.
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Lu, Yi, Huayan Huangfu, Shuguang Zhang, and Shan Fu. "Organizational Risk Dynamics Archetypes for Unmanned Aerial System Maintenance and Human Error Shaping Factors." In Advances in Human Error, Reliability, Resilience, and Performance, 75–87. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20037-4_7.
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Rai, Rajiv Nandan, and Garima Sharma. "Human Reliability Analysis Technique Selection for Life Support Systems Maintenance of Orbital Space Stations Using Fuzzy AHP and ANN." In Advances in Human Error, Reliability, Resilience, and Performance, 128–37. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94391-6_13.
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Ayele, Y., and A. Barabadi. "Human error probability estimation of maintenance activities in cold operating environment based on Bayesian network." In Risk, Reliability and Safety: Innovating Theory and Practice, 938–44. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2016. http://dx.doi.org/10.1201/9781315374987-141.
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"Human Error in Maintenance." In Human Reliability, Error, and Human Factors in Engineering Maintenance, 63–77. CRC Press, 2009. http://dx.doi.org/10.1201/9781439803844.ch5.
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"Human Error in Engineering Maintenance." In Maintainability, Maintenance, and Reliability for Engineers, 185–96. CRC Press, 2006. http://dx.doi.org/10.1201/9781420006780.ch15.
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"Human Error in Aviation Maintenance." In Human Reliability, Error, and Human Factors in Engineering Maintenance, 99–112. CRC Press, 2009. http://dx.doi.org/10.1201/9781439803844.ch8.
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"Human Error in Power Plant Maintenance." In Human Reliability, Error, and Human Factors in Engineering Maintenance, 113–25. CRC Press, 2009. http://dx.doi.org/10.1201/9781439803844.ch9.
Повний текст джерелаТези доповідей конференцій з теми "Reliability, Human error, Railway, Maintenance"
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Cui, Yuanding, Xuelei Meng, and Bingmou Cui. "Human reliability analysis of operation and maintenance of railway signal and communication." In 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), edited by Yongkang Xing. SPIE, 2021. http://dx.doi.org/10.1117/12.2620004.
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Yang, Zaili, Jin Wang, Merzouki Rochdi, and Ouldbouamama Belkacem. "Bayesian modelling for human error probability analysis in CREAM." In 2011 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE). IEEE, 2011. http://dx.doi.org/10.1109/icqr2mse.2011.5976584.
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Ding, Yaonan, Shengkui Zeng, Jianbin Guo, and Meirong Yang. "A Method of Error Mode Effect Analysis for a Human-Computer Interaction System in Aviation." In 2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). IEEE, 2019. http://dx.doi.org/10.1109/qr2mse46217.2019.9021249.
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Rýzek, Dušan, and Martin Bugaj. "Maintenance and reliability of aircraft technology." In Práce a štúdie. University of Zilina, 2021. http://dx.doi.org/10.26552/pas.z.2021.2.36.
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The paper deals with the maintenance and influencing the human factor in aircraft maintenance. The work is divided into three basic parts. In the first part of the paper, the aim was to describe the maintenance from a historical point of view, to describe the individual stages of maintenance and to summarize how to maintain the years of development. We also have specified individual types of maintenance, maintenance intervals. The most extensive part in the theory are the laws and regulations that must comply with when performing maintenance in the Slovak Republic. This part is indeed included, but we consider it important to mention it in the work. The second part of the paper is the analysis of accidents of commercial aircraft in commercial aviation for the last 3 years. The analysis contains 43 accidents, from which we came to a conclusion. In the first part of the analysis, we selected those accidents that occurred due to maintenance, and then from these accidents, we further determined which accidents occurred due to human error in maintenance. The aim was to determine whether the number of accidents in commercial aviation in civil aviation due to maintenance should increase or decrease, and subsequently, whether the number of accidents in terms of human factor inmaintenance would increase or decrease. The last part so the conclusion is of course focused on the evaluation of the results of the analytical part and the declaration of whether we managed to meet the goal of the paper.
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Momin, Geoffrey, Raj Panchal, Daniel Liu, and Sharman Perera. "Case Study: Enhancing Human Reliability With Artificial Intelligence and Augmented Reality Tools for Nuclear Maintenance." In ASME 2018 Power Conference collocated with the ASME 2018 12th International Conference on Energy Sustainability and the ASME 2018 Nuclear Forum. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/power2018-7495.
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Human error accounts for about 60% of the annual power loss due to maintenance incidents in the fossil power industry. The International Atomic Energy Agency reports that 80\% of industrial accidents in the nuclear industry can be attributed to human error and 20\% to equipment failure. The Personal Augmented Reality Reference System (PARRS) is a suite of computer-mediated reality applications that looks to minimize human error by digitizing manual procedures and providing real-time monitoring of hazards present in an environment. Our mission is to be able to provide critical feedback to inform personnel in real-time and protect them from avoidable hazards. PARRS aims to minimize human error and increase worker productivity by bringing innovation to safety and procedural compliance by leveraging technologies such as augmented reality, LiDAR, computer machine learning and particulate mapping using remote systems.
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Passalacqua, Roberto, and Fumiaki Yamada. "Human Reliability and the Current Dilemma in Human-Machine Interface Design Strategies." In 10th International Conference on Nuclear Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/icone10-22061.
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Since human error dominates the probability of failures of still-existing human-requiring systems (as the Monju reactor), the human-machine interface needs to be improved. Several rationales may lead to the conclusion that “humans” should limit themselves to monitor the “machine”. For example, this is the trend in the aviation industry: newest aircrafts are designed to be able to return to a safe state by the use of control systems, which do not need human intervention. Thus, the dilemma whether we really need operators (for example in the nuclear industry) might arise. However, social-technical approaches in recent human error analyses are pointing out the so-called “organizational errors” and the importance of a human-machine interface harmonization. Typically plant’s operators are a “redundant” safety system with a much lower reliability (than the machine): organizational factors and harmonization requirements suggest designing the human-machine interface in a way that allows improvement of operator’s reliability. In addition, taxonomy studies of accident databases have also proved that operators’ training should promote processes of decision-making. This is accomplished in the latest trends of PSA technology by introducing the concept of a “Safety Monitor” that is a computer-based tool that uses a level 1 PSA model of the plant. Operators and maintenance schedulers of the Monju FBR will be able to perform real-time estimations of the plant risk level. The main benefits are risk awareness and improvements in decision-making by operators. Also scheduled maintenance can be approached in a more rational (safe and economic) way.
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Gildersleeve, Matthew, and Christian Wullems. "A Human Factors Investigation Into the Unavailability of Active Warnings at Railway Level Crossings." In 2012 Joint Rail Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/jrc2012-74177.
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This paper discusses human factors issues of low cost railway level crossings in Australia. Several issues are discussed in this paper including safety at level railway crossings, human factors considerations associated with the unavailability of a warning device, and a conceptual model for how safety could be compromised at railway level crossings following prolonged or frequent unavailability. The current paper summarises and extends pertinent literature that must be considered for effective interventions to improve safety and to advance our theoretical understanding of human behaviour at level crossings. Although the results of our research are not presented, we describe our experimental approach to progress the current lack of knowledge in this area. In particular we highlight where we can improve previous research methodology (independent & dependent variables) when investigating right-side failure at level crossings, which can produce results with greater validity and meaning. Our research aims to quantify risk to motorists at level crossings following right-side failure using a Human Reliability Assessment (HRA) method, supported by data collected using an advanced driving simulator. This method aims to identify human error within tasks and task units identified as part of the task analysis process. It is anticipated that by modelling driver behaviour the current study will be able to quantify human reliability. Such a risk assessment for the impact of right-side failure at level crossings is currently absent in the literature. Therefore it is crucial to offer quantification of success and failure of this intricate system. The task analysis allows human error identification for the precursors to risky driving to be achieved. If task analysis is not employed the error reduction method may be unsuitable and eventually unsuccessful. Our aim is also to determine those contexts that allow the system to operate successfully with the smallest probability of human error. Human behaviour during complex tasks such as driving through a level crossing is fundamentally context bound. Therefore this study also aims to quantify those performance-shaping factors that may contribute to vehicle train collisions by highlighting changes in the task units and driver physiology. Finally we consider a number of variables germane to ensuring external validity of our results. Without this inclusion, such an analysis could seriously underestimate risk.
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Timashev, Sviatoslav A. "Human Factor in the Life Cycle and Safety of Machines and Pipelines." In ASME 2003 Pressure Vessels and Piping Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/pvp2003-1919.
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The paper is an overview (using references listed below) and describes the main components, means and methods of a holistic and quantitative human reliability analysis (QHRA) using quantitative values of human error when performing Fault Tree Analysis (FTA) and Event Tree Analysis (ETA). It also deals with qualitative assessment of the influence of the human factor (HF) reliability on safety and risk analysis of potentially dangerous man-machine-structures-environment systems (PDMMSES). Qualitative risk analysis of such man-machine-structures-environment (MMSE) systems is based on using the event-decision technique in combination with a generalized socio-psychological model of the decision making person (DMP). Three types of DMP’s are considered: members of maintenance/repair crews, diagnosticians and different rank DMP’s that operate or own the PDMMSES.
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Timashev, Sviatoslav A., Ludmila V. Polouian, and Zhanna V. Yurchuk. "Role of Human Factor in Pipeline Safety." In 2004 International Pipeline Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ipc2004-0297.
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The paper describes a new method of quantitative assessment of the influence of the human factor (HF) on safety and risk analysis of pipelines throughout their life cycle, based on applied theory of orgraphs (oriented graphs). The paper describes the main components, means and methods of a holistic and quantitative human reliability analysis (QHRA) using quantitative values of human error. Three types of decision making persons (DMP’s) are considered: members of maintenance/repair crews, ILI diagnosticians and different rank DMP’s that operate or own the pipeline. The applied orgraph theory is used to choose, out of a set of possible measures (the effect and cost of implementation of each of them is a known value), a subset of measures that: 1) delivers maximal decrease of the probability of pipeline disaster-type failure or 2) for a given amount of total available financial means, selects a subset of measures that maximizes the decrease of the disaster-type failure. Three real life cases are described: Choosing measures that enhance pipeline ILI results; Minimizing the third party intervention probability; Choosing security measures for an oil pipeline.
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Duffey, Romney B., and John W. Saull. "The Human Bathtub: Safety and Risk Predictions Including the Dynamic Probability of Operator Errors." In 14th International Conference on Nuclear Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/icone14-89476.
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Reactor safety and risk are dominated by the potential and major contribution for human error in the design, operation, control, management, regulation and maintenance of the plant, and hence to all accidents. Given the possibility of accidents and errors, now we need to determine the outcome (error) probability, or the chance of failure. Conventionally, reliability engineering is associated with the failure rate of components, or systems, or mechanisms, not of human beings in and interacting with a technological system. The probability of failure requires a prior knowledge of the total number of outcomes, which for any predictive purposes we do not know or have. Analysis of failure rates due to human error and the rate of learning allow a new determination of the dynamic human error rate in technological systems, consistent with and derived from the available world data. The basis for the analysis is the “learning hypothesis” that humans learn from experience, and consequently the accumulated experience defines the failure rate. A new “best” equation has been derived for the human error, outcome or failure rate, which allows for calculation and prediction of the probability of human error. We also provide comparisons to the empirical Weibull parameter fitting used in and by conventional reliability engineering and probabilistic safety analysis methods. These new analyses show that arbitrary Weibull fitting parameters and typical empirical hazard function techniques cannot be used to predict the dynamics of human errors and outcomes in the presence of learning. Comparisons of these new insights show agreement with human error data from the world’s commercial airlines, the two shuttle failures, and from nuclear plant operator actions and transient control behavior observed in transients in both plants and simulators. The results demonstrate that the human error probability (HEP) is dynamic, and that it may be predicted using the learning hypothesis and the minimum failure rate, and can be utilized for probabilistic risk analysis purposes.