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Готові списки джерел за темами / Reliability, Human error, Railway, Maintenance / Статті в журналах

Щоб переглянути інші типи публікацій з цієї теми, перейдіть за посиланням: Reliability, Human error, Railway, Maintenance.

Статті в журналах з теми "Reliability, Human error, Railway, Maintenance"

Автор: Grafiati

Опубліковано: 10 березня 2023

Оновлено: 19 липня 2025

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1

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 (2022): 4185. http://dx.doi.org/10.3390/s22114185.

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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

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2

Puneetha, Prof. "Railway Track Monitoring System Using Computer Vision." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48665.

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Abstract: Railway track monitoring is a critical aspect of railway infrastructure maintenance, ensuring safe and efficient transportation. Traditional inspection methods often involve manual assessments, which can be time-consuming, labor- intensive, and prone to human error. With advancements in computer vision and artificial intelligence, automated railway track monitoring has emerged as a reliable solution to enhance safety and efficiency. This paper presents a comprehensive analysis of a computer vision-based railway track monitoring system that utilizes image processing and machine learni

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3

Raza, Ali, Rukhshanda Sehar, Abdul Moiz, Ala Saleh Alluhaidan, Sahar A. El-Rahman, and Diaa Salama AbdElminaam. "Novel conditional tabular generative adversarial network based image augmentation for railway track fault detection." PeerJ Computer Science 11 (June 18, 2025): e2898. https://doi.org/10.7717/peerj-cs.2898.

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Railway track fault recognition is a critical aspect of railway maintenance, aiming to identify and rectify defects such as cracks, misalignments, and wear on tracks to ensure safe and efficient train operations. Classical methods for fault detection, including manual inspections and simple sensor-based systems, face significant challenges, such as high labour costs, human error, and limited detection accuracy under varying environmental conditions. These methods are often time-consuming and unable to provide real-time monitoring, leading to potential safety risks and operational inefficiencie

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4

Hrishikesh, Jadhav, Garibe Sangmeshwar, Gavhane Sanghapal, Jadhav Vaibhav, and Prof.A.M.Karanjkar. "Deep Learning Based Railway Track Inspection." Advancement in Image Processing and Pattern Recognition 8, no. 2 (2025): 24–28. https://doi.org/10.5281/zenodo.15279370.

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<em>Railway infrastructure is crucial for transportation, requiring regular inspection to ensure safety and efficiency. Traditional inspection methods rely on manual labor, which is both time- consuming and prone to human error. This project presents a Deep Learning-Based Railway Track Inspection System that leverages ResNet-based Convolutional Neural Networks (CNNs) to automate defect detection in railway tracks. Developed using Python and Tkinter, the system integrates computer vision and deep learning techniques to analyze railway track images and classify them into different defect categor

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5

R, Dr Nelwin Raj N. "Real-Time Railway Track Monitoring Using Yolov8 and Embedded Systems for Automated Defect Detection." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 1856–70. https://doi.org/10.22214/ijraset.2025.68578.

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Abstract: This Railway track monitoring is essential for ensuring the safety, reliability, and longevity of rail transportation infrastructure. Traditional inspection methods such as manual surveys and track circuit-based systems are labour intensive, time consuming, and prone to human error, which results in delayed fault detection and increased maintenance risks. Addressing these challenges, this study presents the Railway Track Monitoring Tool (RT-MT), an intelligent real time defect detection system that integrates machine learning with embedded electronics to enhance railway infrastructur

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6

Sharma, Rajev Kumar, Ajay Sharma, and Sandeep Kanaujia. "Smart Maintenance of Railway Infrastructure Using Wireless Sensor Networks." International Journal of Experimental Research and Review 46 (December 30, 2024): 113–26. https://doi.org/10.52756/ijerr.2024.v46.009.

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The railway infrastructure is a perfect blend of all branches of engineering. Technology has drastically increased, mainly in the Signalling, Civil, Electrical and Mechanical engineering streams. In the field of Signalling, it has leaped from Mechanical to Electronics Interlocking. Civil engineering has gone from manual track maintenance to high-end mechanized tools. In the field of mechanical engineering, it has progressed from wooden coaches to modern designed (LHB)coaches. In electrical engineering, the technology changed from steam loco to diesel and later electrically powered loco design.

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7

Dinmohammadi, Fateme. "A risk-based modelling approach to maintenance optimization of railway rolling stock." Journal of Quality in Maintenance Engineering 25, no. 2 (2019): 272–93. http://dx.doi.org/10.1108/jqme-11-2016-0070.

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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 a

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8

Bogdanova, Valentina E., Anna A. Zakrevskaia, and Vasiliy V. Serikov. "Errors of professional activity of transport system operators in conditions of high information load." Russian Journal of Occupational Health and Industrial Ecology 63, no. 8 (2023): 545–50. http://dx.doi.org/10.31089/1026-9428-2023-63-8-545-550.

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Introduction. Ensuring traffic safety on the railway network involves the development of complex predictive models that take into account both the state of technology and the influence of the "human factor" in order to minimize the risk of erroneous actions and prevent accidents. The study aims to research the mistakes of railway transport operators (using the example of locomotive crew workers). Materials and methods. The authors have conducted the study on the basis of analysis of the database of erroneous actions of employees of locomotive crews (2020–2021), submitted by the Res

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9

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 (2019): 1238–52. http://dx.doi.org/10.1177/0954409719890166.

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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 tr

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10

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.

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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

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11

Fajar, Sodik, Kusrini, and Kusnawi. "Implementation of Machine Learning in Analyzing the Effect of Maintenance on the Reliability of Railway Detection Equipment." Implementation of Machine Learning in Analyzing the Effect of Maintenance on the Reliability of Railway Detection Equipment 8, no. 10 (2023): 7. https://doi.org/10.5281/zenodo.10049761.

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Maintenance is something that must be done on equipment to maintain its reliability. It is necessary to determine the correct maintenance period to make it more effective and efficient so that reliability is maintained while being efficient in terms of costs incurred. This research aims to determine the best algorithm between polynomial regression and Nadaraya Watson kernel regression to determine the maintenance period for train detection equipment and determine the variables that influence the determination of the maintenance period, which has an impact on equipment reliability. Testing the

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12

Janota, Aleš, Rastislav Pirník, Juraj Ždánsky, and Peter Nagy. "Human Factor Analysis of the Railway Traffic Operators." Machines 10, no. 9 (2022): 820. http://dx.doi.org/10.3390/machines10090820.

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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 d

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13

Aliza, M. E. M., A. F. Yusop, M. A. Hamidi, and M. A. M. Nor. "Optimizing Railway Safety by Analyzing Human Reliability Techniques - A review." Journal of Physics: Conference Series 2933, no. 1 (2025): 012014. https://doi.org/10.1088/1742-6596/2933/1/012014.

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Abstract Human reliability analysis (HRA) is a critical component in ensuring the safety and efficiency of railway engineering. As railway systems grow more complex, the methodologies used to assess and improve human reliability must also advance. This review provides a comprehensive analysis of the evolution of HRA, from the first-generation techniques to the third-generation approaches currently in use. Through a broad survey of the literature, comparative analysis, and detailed case studies, this review traces the development of HRA methods, showing the evolution from traditional techniques

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14

Manuilov, N. I. "HUMAN FACTOR INFLUENCE ON TRAIN BRAKE EQUIPMENT RELIABILITY." World of Transport and Transportation 15, no. 3 (2017): 196–204. http://dx.doi.org/10.30932/1992-3252-2017-15-3-19.

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[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

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15

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 (2018): 269. http://dx.doi.org/10.20473/ijosh.v6i3.2017.269-277.

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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

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16

M.S., Ms Bidave. "Railway Track Fault Detection and Automation System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31792.

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The Railway Track Fault Detection and Automation System (RTFDAS) represents a significant leap forward in the realm of railway infrastructure maintenance and management. Traditional methods of track inspection often suffer from limitations such as manual labor, periodic assessments, and the potential for human error, leading to safety hazards and operational disruptions. In response, the RTFDAS leverages cutting-edge technology, sophisticated algorithms, and automation capabilities to enable proactive fault detection and streamlined maintenance processes. This paper presents a comprehensive ov

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17

HAVRYLIUK, V., and S. SHEMANOV. "IMPROVING TRAIN MOVEMENT SAFETY BY USING AUTOMATIC CONTROL OF SIGNAL CURRENT PARAMETERS IN TRACK CIRCUITS." Transport systems and transportation technologies, no. 28 (September 26, 2024): 65–69. http://dx.doi.org/10.15802/tstt2024/312037.

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Purpose. The safety of train traffic largely depends on the functional safety and reliability of railway automation and communication. At the same time, a special role in this belongs to the system of interval regulation of train traffic, which includes autoblocking, automatic locomotive signaling (ALS), driver alertness control systems, hitchhikers. One of the main problems with the current approach to rail lap monitoring is the use of manual measurements, which are expensive, time-consuming and prone to human error. In addition, these manual processes often do not provide the necessary accur

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18

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 (2019): 115. http://dx.doi.org/10.3926/jiem.2702.

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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 fi

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19

Nkosi, Mfundo, Kapil Gupta, and Madindwa Mashinini. "Causes and Impact of Human Error in Maintenance of Mechanical Systems." MATEC Web of Conferences 312 (2020): 05001. http://dx.doi.org/10.1051/matecconf/202031205001.

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The concept of minimizing human error in maintenance is progressively gaining attention in various industries. The incorporation of human factors when solving engineering problems, particularly in maintenance, can no longer be ignored where high standards of performance are expected. The journey of improving maintenance performance through the reduction of human error begins with the understanding of causes and impact of human error in maintenance. This paper evaluates previous scholarly writings on human errors, to specifically establish the causes and impact of human error in maintenance. Th

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20

Sheikhalishahi, Mohammad, Liliane Pintelon, and Ali Azadeh. "Human factors in maintenance: a review." Journal of Quality in Maintenance Engineering 22, no. 3 (2016): 218–37. http://dx.doi.org/10.1108/jqme-12-2015-0064.

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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

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21

Singh, Sarbjeet, Rupesh Kumar, and Uday Kumar. "Applying human factor analysis tools to a railway brake and wheel maintenance facility." Journal of Quality in Maintenance Engineering 21, no. 1 (2015): 89–99. http://dx.doi.org/10.1108/jqme-03-2013-0009.

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Purpose – The purpose of this paper is to demonstrate three techniques to extract human factor information from specific railway maintenance tasks. It describes the techniques and shows how these tools can be applied to identify improvements in maintenance practices and workflow. Design/methodology/approach – Three case studies were conducted on single group of technicians (n=19) at a railway maintenance workshop in Luleå, Sweden. Case study I examined the posture of the technicians while they were changing the brake shoes of freight wagons; the study employed the Standard Nordic Questionnaire

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22

Zhao, Zhonghao, Boping Xiao, Naichao Wang, Xiaoyuan Yan, and Lin Ma. "Selective Maintenance Optimization for a Multi-State System Considering Human Reliability." Symmetry 11, no. 5 (2019): 652. http://dx.doi.org/10.3390/sym11050652.

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In an actual industrial or military operations environment, a multi-state system (MSS) consisting of multi-state components often needs to perform multiple missions in succession. To improve the probability of the system successfully completing the next mission, all the maintenance activities need to be performed during maintenance breaks between any two consecutive missions under limited maintenance resources. In such case, selective maintenance is a widely used maintenance policy. As a typical discrete mathematics problem, selective maintenance has received widespread attention. In this work

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23

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.

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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 maintena

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24

Ogmen, Akide Cerci, and Ismail Ekmekci. "HEART Hybrid Methods for Assessing Human Reliability in Coal-Fired Thermal Power Plant Process." Sustainability 14, no. 17 (2022): 10838. http://dx.doi.org/10.3390/su141710838.

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The assessment of human reliability is crucial in serious processes and operations, such as planned maintenance, unplanned maintenance, and troubleshooting in a coal-fired thermal power plant, as the nature of these processes poses significant threats. When the literature is examined, the evaluation of human reliability in any type of power plant, especially coal-fired thermal power plants, is limited. In order to fill this gap, we systematically assessed human reliability in an accident that occurred during a repair of a tube failure in a boiler in a coal-fired thermal power plant. The HEART

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25

Emami-Mehrgani, Behnam, Sylvie Nadeau, and Jean-Pierre Kenné. "Optimal lockout/tagout, preventive maintenance, human error and production policies of manufacturing systems with passive redundancy." Journal of Quality in Maintenance Engineering 20, no. 4 (2014): 453–70. http://dx.doi.org/10.1108/jqme-10-2012-0035.

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Purpose – The analysis of the optimal production and preventive maintenance with lockout/tagout planning problem for a manufacturing system is presented in this paper. The considered manufacturing system consists of two non-identical machines in passive redundancy producing one type of part. These machines are subject to random breakdowns and repairs. The purpose of this paper is to minimize production, inventory, backlog and maintenance costs over an infinite planning horizon; in addition, it aims to verify the influence of human reliability on the inventory levels for illustrating the import

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26

Quiroga, L. M., and E. Schnieder. "Monte Carlo simulation of railway track geometry deterioration and restoration." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 226, no. 3 (2011): 274–82. http://dx.doi.org/10.1177/1748006x11418422.

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Travelling safely and comfortably on high-speed railway lines requires excellent conditions of the whole railway infrastructure in general and of the railway track geometry in particular. The maintenance process required to achieve such excellent conditions is complex and expensive, demanding a large amount of both human and technical resources. In this framework, choosing the right maintenance strategy becomes a critical issue. A reliable simulation of the railway geometry ageing process would offer a great advantage for the optimization of planning and scheduling of maintenance activities. A

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Dr., Rajashree Thosar, Thosar Dr.Devidas, Tambale Adarsh, Tapre Piyush, and Satpute Shraddha. "Accident Prevention of Train & Track Fault." Journal of Advancement in Software Engineering and Testing 8, no. 2 (2025): 16–22. https://doi.org/10.5281/zenodo.15273576.

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<em>This project focuses on enhancing railway safety by developing an automated system to prevent accidents caused by unmonitored crossings and undetected track cracks. The system uses infrared (IR) sensors for automated railway gate control and crack detection, with data processed by an Arduino microcontroller. When a crack is detected, GPS and GSM modules relay the location to the control room. The automation of gates and real-time crack monitoring aims to reduce human error and improve safety. Implementing this system on a large scale could significantly minimize railway accidents and enhan

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Kwon, Hwi-Jin, Seung-Il Lee, Ju-Hyung Park, and Chul-Su Kim. "Design of Augmented Reality Training Content for Railway Vehicle Maintenance Focusing on the Axle-Mounted Disc Brake System." Applied Sciences 11, no. 19 (2021): 9090. http://dx.doi.org/10.3390/app11199090.

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Light maintenance training for electric multiple-unit components of the organization of railway operations is generally conducted using maintenance manuals and work videos, following the guidelines of each organization. These manuals are in the form of booklets, complicated and inconvenient for maintenance operators to carry. Therefore, training content that visualizes maintenance procedures in a three-dimensions (3D) space is necessary to overcome the drawbacks of booklet-type training. In this study, we developed augmented reality (AR)-based training content for railway vehicle maintenance t

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Luan, Rui, and Rengkui Liu. "Risk Assessment Model for Railway Track Maintenance Operations Based on Combined Weights and Nonlinear FCE." Applied Sciences 15, no. 13 (2025): 7614. https://doi.org/10.3390/app15137614.

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Current risk assessment in railway track maintenance operations faces challenges (low spatiotemporal accuracy, limited adaptability to various scenarios, and tendency of linear fuzzy comprehensive evaluation (FCE) methods to underestimate high-risk factors). To address these, this study proposes a novel risk assessment model that integrates subjective–objective weighting techniques with a nonlinear FCE approach. By incorporating spatiotemporal information, the model enables precise localization of risk occurrence in individual maintenance operations. A comprehensive risk index system is constr

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Poliński, Janusz. "Diagnostics of Track Infrastructure as Part of the Digitisation of Russian Railways." Problemy Kolejnictwa - Railway Reports 64, no. 188 (2020): 149–60. http://dx.doi.org/10.36137/1886e.

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Technical diagnostics is an integral part of the railway maintenance process. Through timely maintenance, in addition to ensuring the safety, functional and technical reliability of the infrastructure, maintenance costs are reduced and downtime losses, due to failures or premature repair requests, are eliminated or reduced. The track infrastructure diagnostic tools have evolved. This is related to, among others, the miniaturisation of instruments, reading accuracy during motion, as well as upgraded measurement automation and result analysis. Currently, data obtained from multifunctional diagno

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31

DHILLON, B. S. "MEDICAL EQUIPMENT RELIABILITY: A REVIEW, ANALYSIS METHODS AND IMPROVEMENT STRATEGIES." International Journal of Reliability, Quality and Safety Engineering 18, no. 04 (2011): 391–403. http://dx.doi.org/10.1142/s0218539311004317.

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This paper presents facts and figures, directly or indirectly, related to medical equipment reliability and reviews various important aspects, directly or indirectly, concerned with medical equipment reliability including classifications of medical devices/equipment, human error in medical equipment, useful guidelines for reliability and other professionals to improve medical equipment reliability, and medical equipment maintenance. A number of methods considered useful for performing medical equipment reliability analysis are also presented. Useful sources and organizations for obtaining medi

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Mahmood, Bilawal, and Seok Kim. "Framework of Scan to Building Information Modeling for Geometric Defect Localization in Railway Track Maintenance." Buildings 14, no. 11 (2024): 3578. http://dx.doi.org/10.3390/buildings14113578.

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Railway transportation plays a vital role in modern society, enabling the safe and efficient movement of people and goods over long distances. To ensure the longevity and safety of a railway infrastructure, the regular maintenance of tracks is crucial. Traditional track inspections, conducted manually to monitor geometric parameters and to identify defects, are time-consuming, labor-intensive, and prone to human error. Current Scan-to-BIM frameworks for railway maintenance also lack standardized methods for extracting geometric parameters that can be easily integrated into Building Information

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Fuqaha, Sameh. "Railway safety research: Mapping trends, strategic clusters, and future pathways." Journal of Railway Transportation and Technology 4, no. 1 (2025): 17–34. https://doi.org/10.37367/jrtt.v4i1.55.

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This study presents a comprehensive bibliometric analysis of railway safety research from 2019 to 2024, offering critical insights into the thematic evolution, intellectual structure, and future pathways in this vital domain. By analyzing 445 peer-reviewed articles retrieved from leading academic databases, the study identifies major research clusters centered around risk assessment, human factors, and AI-enabled infrastructure monitoring. The findings reveal a significant shift toward intelligent safety systems, with deep learning, predictive maintenance, and human reliability modeling emergi

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Plesner, Andreas, Allan P. Engsig-Karup, and Hans True. "Detecting Railway Track Irregularities with Data-driven Uncertainty Quantification." Highlights of Vehicles 3, no. 1 (2025): 1–14. https://doi.org/10.54175/hveh3010001.

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This study addresses the critical challenge of assessing railway track irregularities using advanced machine learning techniques, specifically convolutional neural networks (CNNs) and conformal prediction. Leveraging high-fidelity sensor data from high-speed trains, we propose a novel CNN model that significantly outperforms state-of-the-art results in predicting track irregularities. Our CNN architecture, optimized through extensive hyperparameter tuning, comprises multiple convolutional layers with batch normalization, Exponential Linear Unit (ELU) activation functions, and dropout regulariz

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Kohl, Linus, Sarah Eschenbacher, Philipp Besinger, and Fazel Ansari. "Large Language Model-based Chatbot for Improving Human-Centricity in Maintenance Planning and Operations." PHM Society European Conference 8, no. 1 (2024): 12. http://dx.doi.org/10.36001/phme.2024.v8i1.4098.

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The recent advances on utilizing Generative Artificial Intelligence (GenAI) and Knowledge Graphs (KG) enforce a significant paradigm shift in data-driven maintenance management. GenAI and semantic technologies enable comprehensive analysis and exploitation of textual data sets, such as tabular data in maintenance databases, maintenance and inspection reports, and especially machine documentation. Traditional approaches to maintenance planning and execution rely primarily on static, non-adaptive simulation models. These models have inherent limitations in accounting for dynamic environmental ch

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Hololobova, O. O., S. Y. Buriak, V. I. Havryliuk, R. V. R. V. Markul, A. M. Afanasov, and D. S. Bilukhin. "Determination of the Origin of Failures in the Operation of the Automatic Locomotive Signaling." Science and Transport Progress, no. 6(96) (December 20, 2021): 5–13. http://dx.doi.org/10.15802/stp2021/257914.

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Purpose. The safety of the transportation process in railway transport and its continuous operation to a large extent depend on the reliability of the means of railway automation and communication. In this case, special role in ensuring the efficient and safe operation of railways belongs to the systems of interval control of the train movement, as well as automatic locomotive signaling in conjunction with the systems of monitoring the driver's vigilance and automatic train stop. Therefore, the main purpose of the article is a detailed analysis of the operation reliability of these systems, in

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Li, Wenhao, Tao Li, Xiaoqing Zhou, and Xian Liu. "Application of LuTan-1 SAR Data in Railway Subsidence Monitoring." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1-2024 (May 10, 2024): 351–57. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-2024-351-2024.

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Abstract. InSAR technology is currently a crucial tool for large-scale surface deformation monitoring, particularly excelling in regional subsidence monitoring. In this study, focusing on the Jinan section of the Shandong railway, newly launched LUTAN-1 satellite SAR data was employed. DInSAR and Stacking techniques were applied to analyze the subsidence in response to the long-term operation load of high-speed trains and surrounding human activities. Through the analysis of data from June 2023 to December 2023, regional subsidence was identified in this section, with a subsidence rate reachin

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Kaur, Gurleen, and Bhavika Moza. "Exploring Railway Forensics: Top Approaches And Future Directions." Asian Journal Of Science And Technology 14, no. 6 (2023): 12561–67. https://doi.org/10.5281/zenodo.8428490.

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Railway incidents can have significant safety implications for the railway system, its components, and the people involved, leading to train delays and financial losses. Railway forensic investigations play a crucial role in understanding the causes and circumstances of these accidents. This field is continuously evolving and offers scope for improvement. Various organizations are responsible for conducting thorough railway examinations, highlighting the importance of their expertise in investigations. Examining rolling stock is essential for analyzing train conditions and performance. Track a

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Singh, Sarbjeet, and Rupesh Kumar. "Evaluation of Human Error Probability of Disc Brake Unit Assembly and Wheel Set Maintenance of Railway Bogie." Procedia Manufacturing 3 (2015): 3041–48. http://dx.doi.org/10.1016/j.promfg.2015.07.849.

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Singh, Sarbjeet, Rupesh Kumar, and Uday Kumar. "Modelling factors affecting human operator failure probability in railway maintenance tasks: an ISM-based analysis." International Journal of System Assurance Engineering and Management 6, no. 2 (2014): 129–38. http://dx.doi.org/10.1007/s13198-014-0255-0.

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Popov, Anton Nikolaevich, and Mariya Leonidovna Popova. "Monitoring the integrity of rails by flowing current." Transport of the Urals, no. 3 (2023): 79–83. http://dx.doi.org/10.20291/1815-9400-2023-3-79-83.

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Violations of the integrity of rails on railway sections pose a serious threat to traffic safety, cause accidents and wrecks, lead to significant economic damage and human casualties. The integrity of rails is controlled by flaw detection methods, as well as by a special mode of operation of rail circuits due to the signal current flow around track circuits. The widespread use of AC rail circuits which reliably perform the control mode made it possible to organize a simple method of integrity control over a significant length of railway lines. The complexity of maintenance and low reliability

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Alif, Mujadded Al Rabbani, and Muhammad Hussain. "Lightweight Convolutional Network with Integrated Attention Mechanism for Missing Bolt Detection in Railways." Metrology 4, no. 2 (2024): 254–78. http://dx.doi.org/10.3390/metrology4020016.

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Railway infrastructure safety is a paramount concern, with bolt integrity being a critical component. In the realm of railway maintenance, the detection of missing bolts is a vital task that ensures the stability and safety of tracks. Traditionally, this task has been approached through manual inspections or conventional automated methods, which are often time-consuming, costly, and prone to human error. Addressing these challenges, this paper presents a state-of-the-art solution with the development of a lightweight convolutional neural network (CNN) featuring an integrated attention mechanis

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Aju kumar, V. N., and O. P. Gandhi. "Quantification of human error in maintenance using graph theory and matrix approach." Quality and Reliability Engineering International 27, no. 8 (2011): 1145–72. http://dx.doi.org/10.1002/qre.1202.

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Shen', Czei, and Aleksey Caplin. "Application of Non-Destructive Testing Technology on Rolling Stock and Prospects for Its Development." Bulletin of scientific research results 2025, no. 1 (2025): 31–44. https://doi.org/10.20295/2223-9987-2025-1-31-44.

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Purpose: The article is devoted to the research of the integration of innovative technologies into non-destructive testing (NDT) systems on the railway rolling stock. Traditional NDT methods, such as ultrasonic, magnetic particle and eddy current inspection, as well as their potential and limitations are considered in the light of modern requirements to safety and operational efficiency. The focus is on the application of smart glasses and machine vision technologies as supporting tools for improving diagnostics accuracy, faster defect detection and better experts’ interaction. Smart glasses a

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Asadzadeh, S. M., and A. Azadeh. "An integrated systemic model for optimization of condition-based maintenance with human error." Reliability Engineering & System Safety 124 (April 2014): 117–31. http://dx.doi.org/10.1016/j.ress.2013.11.008.

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Okirie, Ahiamadu Jonathan, Mack Barnabas, and Justice Efam Adagbon. "Maintenance Management Optimization: Evaluating Manual and Automated Methods of Tracking Uptime Hours for Offshore Equipment." American Journal of IR 4.0 and Beyond 3, no. 1 (2024): 15–27. http://dx.doi.org/10.54536/ajirb.v3i1.3516.

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Offshore oil and gas fields are among the largest contributors to global oil and gas production. The reliable functioning of these facilities relies heavily on the reliability of the process equipment. Managing and operating offshore equipment is inherently complex, requiring careful planning to ensure maximum uptime and minimal downtime. This study addresses a significant gap in knowledge by comparing the effectiveness of manual and automated methods for tracking the uptime hours of offshore equipment. Using a mixed-methods approach that incorporates quantitative and comparative data analysis

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A., Kavithamani, Aakash S., Krithick Roshan V., Shobana S., Vigneshwari V., and Nithish Ram K S. "Arduino UNO based Autonomous Train System." Journal of ISMAC 7, no. 1 (2025): 79–93. https://doi.org/10.36548/jismac.2025.1.006.

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This study presents the design and implementation of an “Autonomous Train System” intended to improve safety, efficiency, and reliability in modern railway operations. The proposed system integrates advanced technologies, including GPS modules, infrared and ultrasonic sensors, RF communication, and microcontroller-based control units to facilitate real-time obstacle detection, automatic braking, and inter-train communication. By continuously monitoring track conditions and nearby trains, the system can dynamically determine risk and execute timely responses, significantly reducing the chance o

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Shafique, Rahman, Hafeez-Ur-Rehman Siddiqui, Furqan Rustam, et al. "A Novel Approach to Railway Track Faults Detection Using Acoustic Analysis." Sensors 21, no. 18 (2021): 6221. http://dx.doi.org/10.3390/s21186221.

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Regular inspection of railway track health is crucial for maintaining safe and reliable train operations. Factors, such as cracks, ballast issues, rail discontinuity, loose nuts and bolts, burnt wheels, superelevation, and misalignment developed on the rails due to non-maintenance, pre-emptive investigations and delayed detection, pose a grave danger and threats to the safe operation of rail transport. The traditional procedure of manually inspecting the rail track using a railway cart is both inefficient and prone to human error and biases. In a country like Pakistan where train accidents hav

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Ng, Yang Siong Robson, and Hamad Rashid. "Enhancing human performance reliability in aircraft pushback operations." International Journal of Quality & Reliability Management 36, no. 4 (2019): 485–509. http://dx.doi.org/10.1108/ijqrm-01-2018-0008.

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Purpose The purpose of this paper is to investigate the aircraft pushback operations to predict and manage human errors, particularly those associated with the complex team work of carrying out the pushback operation. This should improve air ramp operations reliability. Design/methodology/approach The study applied the human reliability assessment “Systematic Human Error Reduction and Prediction Approach” that involved a total of 60 semi-structured interviews with practicing experts. Past ramp accident reports were also reviewed to provide more in-depth insights to the problem. Findings Some o

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Keprate, Arvind, Stine Kilskar, and Pete Andrews. "Towards Efficient Operation and Maintenance of Wind Farms: Leveraging AI for Minimizing Human Error." PHM Society European Conference 8, no. 1 (2024): 9. http://dx.doi.org/10.36001/phme.2024.v8i1.4067.

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To effectively compete with other renewable energy sources, there remains a critical need to further decrease the Levelized Cost of Energy of Wind Farms (WFs). A promising way to achieve this objective is by minimizing the downtime of wind turbines (WTs) through effective Inspection and Maintenance (I&M) activities. Conventionally, I&M plans have predominantly relied on CM/SCADA data obtained from the physical components of turbines, with data analytics and machine learning (ML) techniques being employed to predict their performance and maintenance needs. However, statistics indicate t

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