A framework is presented to evaluate the safety and availability of the railway operation, and quantifying the probability of the signalling system not to supervise the railway traffic. Since a failure of the signalling systems still allows operation of the railway, it is not sufficient to study their effect on the railway operation by considering only the failures and delays. The safety and availability are evaluated, handling both repairs and replacements by using a Markov model. The model is verified with a case study of Swedish railway signalling systems with different scenarios. The results show that the probability of being in a state where operation is possible in a degraded mode is greater than the probability of not being operative at all, which reduces delays but requires other risk mitigation measures to ensure safe operation. The effects that different improvements can have on the safety and availability of the railway operation are simulated. The results show that combining maintenance improvements to reduce the failure rate and increase the repair rate is more efficient at increasing the probability of being in an operative state and reducing the probability of operating in a degraded state.

Signalling systems ensure the safe operation of the railway network. Their reliability and maintainability directly affect the capacity and availability of the railway network, in terms of both infrastructure and trains, as a line cannot be fully operative until a failure has been repaired. The purpose of this paper is to propose a data-driven decision support model which integrates the various parameters of corrective maintenance data and to study maintenance performance by considering different RAMS parameters. This model is based on failure analysis of historical events in the form of corrective maintenance actions. It has been validated in a case study of railway signalling systems and the results are summarised. The model allows the creation of maintenance policies based on failure characteristics, as it integrates the information recorded in the various parameters of the corrective maintenance work orders. The model shows how the different failures affect the dependability of the system: the critical failures indicate the reliability of the system, the corrective actions give information about the maintainability of the components, and the relationship between the corrective maintenance times measures the efficiency of the corrective maintenance actions. All this information can be used to plan new strategies of preventive maintenance and failure diagnostics, reduce the corrective maintenance, and improve the maintenance performance.

The purpose of this paper is to evaluate the safety and availability of railway signalling systems using Markov models. Since a failure of the signalling systems still allows operation of the railway, it is not sufficient to study their safety and availability by considering only the failures and delays. The safety and availability are evaluated, handling both repairs and replacements by using a Markov model. The model is validated with a case study of Swedish railway signalling systems with different scenarios. The results obtained show that the probability of being in a state where operation is possible in a degraded mode is greater than the probability of not being operative at all, which reduces delays but requires other risk mitigation measures to ensure safe operation.

Railway signalling systems can be considered a group of complex systems that together provide control, supervision and protection of railway operation. When a failure occurs in the railway signalling system, other safety mitigation measures are put into place to continue railway operation, e.g. reduced speed, with the driver responsible for safe operation. Briefly stated, failures of the railway signalling system affect both the capacity and safety of the railway. The purpose of this study is to propose tools to assess the dependability and safety of infrastructure signalling systems in the operation and maintenance phase, to support continuous improvement.The overall research strategy is a case study at Trafikverket (Swedish transport administration). Quantitative data have been collected through the fault reporting system (0Felia) for a specific railway line and through interviews, document studies, and observations. The type of failure is either random or systematic, according to the railway standards. The analysis of random failures is based on a theoretical framework of RAMS (Reliability, Availability, Maintainability, and Safety) for signalling systems. Failure data have been analysed using such methodologies as FMECA (Failure, Mode, Effects, and Criticality Analysis), Markov analysis, and reliability analysis for repairable systems. Systematic failure data analysis is based on theories and expert judgement in the area of configuration management and information logistics. The results of the study can be divided into two parts. The first part comprises three tools that can be used to assess the dependability and safety performance of railway infrastructure signalling systems based on random failure data. The first tool in this section adapts the FMECA logic in an analysis model to assess the operational RAMS performance for different levels of infrastructure signalling systems. The second tool combines statistical methods with expert assessment to perform a reliability assessment of complex long-lived repairable systems, such as railway signalling systems. The third tool evaluates the safety and availability of the railway operation based on the state of signalling systems. The second part of the study is a guide on how to apply configuration management and information logistics to deal with systematic failures related to infrastructure signalling systems.These tools can be used during the operation and maintenance phases to assess the dependability and safety of a signalling system in the railway infrastructure. For example, the FMECA-based tool reveals that a maintenance approach based on the causes of failures instead of particular systems can be more appropriate to support improvement of the maintenance of railway signalling systems. The results obtained from the case study show the importance of external influences on the dependability of signalling systems and the need to improve the quality of collected data. This was manifested by a high variability of the reliability and maintainability of different systems with the same architecture and operational characteristics. This has two implications for the study. First, it shows the focus of the adapted tools to analyse failures must be on a system level, instead of on more detailed indenture levels. Second, it suggests how to improve maintenance support by enhancing the configuration management and information logistics. The results can be used improve the management of all types of failures, thereby reducing risks and supporting the safety integrity of signalling systems.

Railway signalling systems are composed of several different systems; each has its own purpose, but the main functionality of the overall system is determined by the interoperability between them. Railway signalling systems ensure the safe operation of the railway network, and their reliability and maintainability directly affect the capacity and availability of the railway network, in terms of both infrastructure and trains. The functionality of the signalling system is based on the principle of “fail safe”; this means that the railway section where a failure is located will be not fully operative until the failure is repaired (since safety cannot be ensured). Hence, the dependability of these systems directly affects the capacity of the network.Signalling systems take up a large part of the railway’s overall corrective maintenance. Railway managers need to have a holistic view of all systems to optimise maintenance. Signalling systems are especially important, given the need for interoperability. Given their complexity, knowledge must be correctly managed to ensure proper performance in all phases of the life cycle. Enhancing information logistics would lead to considerable improvements in this area. This licentiate analyses the dependability and maintenance of railway signalling systems and proposes various approaches to improve maintenance performance. External factors affecting the reliability of signalling systems are identified, such as their location. The signalling system is treated as a system of systems because of its interoperability and because failures occurring on different systems can be associated with the same failure effect. A data driven model for maintenance decision support is proposed, based on corrective maintenance work orders. The data driven model allows a holistic perspective of failure occurrence, as it integrates the information recorded in the many different parameters of the corrective maintenance work orders. With this model, existing maintenance policies could be reviewed and improved upon. This thesis proposes a model for configuration management, which simplifies the access and visibility of information. The model manages the change control process and ensures that configurations are updated in real-time. An enhancement of the configuration management has the potential to increase the efficacy of the maintenance actions in signalling systems by improving the accessibility of the information required to understand possible future failures. With increased accessible knowledge, the time needed to identify failures can be reduced, resulting in greater maintenance efficiency. It also establishes a framework for improving inter-organisational knowledge management between stakeholders, resulting in the creation of a holistic perspective of the maintenance and operation of the railway network, avoiding the loss of knowledge linked to outsourcing, and improving the effectiveness of the organisations involved.

The railway network is a complex system with several technologies and a multitude of stakeholders working together to solve problems created by the increasing demands on capacity, speed and mobility for the transportation of goods and passengers. However, the presence of many different stakeholders complicates knowledge management and transfer. The purpose of this paper is to analyse the potential for improving inter-organisational knowledge management in the maintenance of railway signalling systems and make concrete suggestions for improvements. Even if information logistics processes can disseminate explicit knowledge on the maintenance of railway signalling systems, they cannot handle the tacit knowledge transfer that often is crucial. The study finds considerable potential for improving the knowledge management process. It suggests possible measures and makes suggestions for future studies.

The reliability, maintainability and related maintenance support of signalling systems affect the railway network´s availability. Constituting a system-of-systems spread over a wide geographical area, signalling systems consist of a large number of items with different lifecycles making it a challenge to define and describe the structure and relationship between the system’s inherent items at any specific time. System configuration describes a system’s structure to which other data sources can be related. Some current research discusses asset maintenance management in the railway infrastructure, but not many holistic approach deals with signalling systems. The purpose of this paper is to investigate how the process of configuration management, can improve the dependability of the railway system. The paper presents a model for the configuration management of railway signalling systems. The model is based on the results of company surveys and interviews, data analysis and literature review. This model provides better control and visibility of the information related to the system and any changes made to it. Faster and better failure diagnostics can be performed, thus improving maintenance performance. This, in turn, provides better availability of the system by reducing the downtime of the railway network; hence, an improvement in maintainability is also achieved.

The purpose of this paper is to explore the use of information logistics for railway signalling systems to improve the efficiency of their corrective maintenance. The signalling system is used to control, supervise and protect railway traffic; therefore, its reliability, maintainability and related maintenance support affect the availability of the railway network. The paper reviews the current status of the maintenance of railway signalling systems, looking at company surveys and company data for a specific case study and consulting relevant literature. It describes how and where data are processed and analyses corrective maintenance work orders to determine how much time is spent on corrective action and knowledge management Areas of improvement are identified and possible improvements are proposed. The efficiency of information logistics has a clear effect on the dependability of the railway signalling system. Signalling systems’ performance can be improved by having better control of and accessibility to the information required for each maintenance action.

Signalling systems in railway allow the control, supervision and protection of railway traffic. These systems play an important part in a railway’s capacity and availability. Thus, their reliability and maintenance are key concerns. A number of signalling systems are on the market today; these work to guarantee safety while meeting the required capacity of the network. In order to keep the railway network in an optimal state, it is critical for the signalling systems to have tools that can make data mining and analysis easier and faster. The solution described herein allows data mining and posterior analysis without depending on the elements that provide the data. This is a key factor for signalling systems, due to their complexity and continuous development. For integration purposes, a data collection and distribution system based on the concept of cloud computing is proposed to collect data or information pertaining to the assets of the railway signalling systems. From a maintenance point of view, a benefit is that information or data may be collected pertaining to the health, variability, performance or utilization of an asset.