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Guest Editorial

Volume 11, Number 2, March 2015 - Guest Editorial - pp. 105-106


Transport systems and infrastructure form critical elements of modern society. It is essential that such systems operate efficiently and reliably in order to move people and goods to their destinations in a safe and cost effective manner. When such systems experience operational failures they cause disruption and inconvenience, and in the worst cases can result in injuries and fatalities. As the population increases, the demands on the transport systems also increase.

Any transport system, be it road, rail, air or water, is more efficient the larger the percentage of its time it is operational and therefore generating an income. A difficulty with this operating practice is scheduling the times for essential preventive maintenance. The proper maintenance practices will minimise the occurrence of breakdowns necessitating reactive maintenance. An added consideration is that many transport systems feature aging infrastructure.

From the safety point of view, whilst transport systems usually have high levels of safety, their design, operation, and maintenance have to be controlled adequately in order to ensure this state. Modelling techniques should be used to predict the effectiveness of the asset management strategy employed for transport systems and also to predict the risk to the passengers, workforce and general public that they pose.

This special issue contains a number of articles that are focussed on transport system asset management, reliability and safety.

The first paper by Rama and Andrews investigates the advantages of analysing the railway network as a multi-asset system, when a Petri Net model is developed and analysed using the Monte Carlo simulation method. The model is used to predict the network performance and obtain the information to support asset management decisions.

The second paper by Fink et al. propose an algorithm of Deep Belief Networks to predict operational disruptions caused by train door systems and demonstrate its performance using a European railway fleet data.

A road maintenance management system is presented in the third paper by Yang et al., where an optimal strategy of maintenance and reconstruction works on a highway network can be found using the method of Genetic Algorithms. Pavement age gain models are developed for the evaluation of pavement condition over time due to maintenance.

In the fourth paper by Hackl et al. focuses on risk evaluation of infrastructure networks due to natural hazards. Due to the complex interdependency of the infrastructure systems such events, albeit rare, can have a devastating impact. The authors propose to use an overarching risk assessment process across a number of modules for individual systems which interact and the process is demonstrated in a case study for an example region in Switzerland.

The fifth paper by Stoop and van Kleef considers air transport systems as socio-technical systems and suggests that the increased complexity and interdependency of the infrastructure systems requires novel notions for reliability, control over operational performance and safety assessment. Incorporating the operator performance characteristics during the response to failures is of vital importance in capturing the overall behaviour of such systems and in dealing with potentially catastrophic consequences.

Finally, in the sixth article, van Dongen offers a perspective of maintenance engineering when the calculations of life expectancy of an asset are integrated in the initial design of new assets and the maintenance and modernisation of the current ones. Real-time asset condition monitoring furnishes maintenance teams with more accurate information and supports proactive dynamic maintenance scheduling, which poses a challenge in terms of maintenance logistics but can lead to a reduced number of unexpected failures. Overall, these articles present some of the latest developments and future trends in the area of asset management, reliability and safety across the different transport sectors.

The Guest Editors would like to thank all of the authors for their contributions in this special issue and the reviewers for their time in providing the authors with constructive feedback. We would also like to thank the Editor-in-Chief, Professor Krishna B. Misra, and the editorial team who worked on the publication of this special issue.


Rasa Remenyte-Prescott is The Lloyd’s Register Foundation Lecturer in Risk and Reliability Engineering in Nottingham Transportation Engineering Centre at the University of Nottingham (which helps protect life and property by supporting engineering-related education, public engagement and the application of research). Rasa gained BSc and MSc degrees with distinction in mathematics from Kaunas University of Technology, Lithuania. Following this Rasa undertook her Doctorate research at Loughborough University on systems reliability modelling of non-coherent systems using the Binary Decision Diagram technique. Rasa’s research interests involve reliability modelling techniques for engineering systems and healthcare safety, infrastructure asset management methods for railways and highways and fault diagnostics techniques. She is the author of around 30 research papers on these topics.


John D. Andrews is the Royal Academy of Engineering and Network Rail Professor of Infrastructure Asset Management in the Nottingham Transportation Engineering Centre at the University of Nottingham, U.K. He is also Director of The Lloyd’s Register Foundation Centre for Risk and Reliability Engineering. Prior to this position he worked for 20 years in the Department of Aeronautical and Automotive Engineering at Loughborough University where his final post was Professor of Systems Risk and Reliability. The prime focus of his research has been on methods for predicting system reliability in terms of the component failure probabilities and a representation of the system structure. Much of this work has concentrated on the Fault Tree technique and the use of the Binary Decision Diagrams (BDDs) as an efficient and accurate solution method. Recently attention has turned more the degradation modelling and the effects of maintenance, inspection and renewal on asset performance. He is the author of over 200 research papers. He is also one of the Editors-in-Chief of IJPE. He is also Editor-in-Chief of Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. 


Lisa Jackson (Ph.D.) is a Senior Lecturer in Risk and Reliability, in the Department of Aeronautical and Automotive Engineering, Loughborough University, England since 2010. She has taught at this university since 2001. She has published extensively in the area of Reliability and Risk in several international Journals. Her research interests include Applications of Reliability Methods for enhanced reliability performance, Fault Diagnostics and Prognosis, Crime Reduction through Demand Modelling and Positioning, Vehicle Safety and Hazard Analysis. She is on the Editorial Board of the International Journal of Performability Engineering and of the IMechE Part O: Risk and Reliability Journal. 


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