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.

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.

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.

The railway network composed by different systems, such assignalling, power supply, rolling stock and others. The signalling system is used for control, supervision and protection of railway traffic. Its reliability, maintainability and related maintenance support affect the availability of the railway network. Often,signalling system itself is considered as a system-of-systems spread over a wide geographical area and consists of a large number of items with different lifecycle. However, managing a complex technical system with large number of items in different lifecycle phases to achieve required availability is challenging. One major challenge is to define and describe the structure and relation between the system’s inherent items at any specific period of time, i.e. the configuration of the system. The system configuration is important during the design and manufacturing of systems, but it is also essential during the utilisation and retirement of a system. Furthermore, system configuration can be considered as an essential data container to which other data sources can be related, e.g. design data, reliability data, maintainability data, operation data, and maintenance data. Aproper management of configuration data is highly important during a system’s whole lifecycle, e.g. the railway signalling system. Hence, the purpose of this paper is investigate how the process of configuration management related to railway signalling system can be improved through utilisation of Capability Maturity Model Integrated (CMMI).

The occurrence of equipment failures is one of the main causes of inefficiency. These events increase the operational costs and give rise to a loss of revenues or in the worst case they can even produce an accident with significant damages to people and the environment. The efficiency of the operation of an industrial installation in a given period of time has been defined use the ratio of the Dependability level achieved by the installation in a specified period of time and the sum of the corresponding Dependability and Undependability costs.

The aim of this paper is the development of a methodology for the calculation of operating costs in industrial facilities that addresses the difficulty of performing a simple, homogeneous and objective evaluation of the operational efficiency of the industrial facility. The main obstacle to this evaluation is the lack of a method for quantifying Dependability, which to date has always been considered a purely qualitative characteristic.

Several studies in Sweden have looked into railway electromagnetic interference (EMI) either to discover the source of the interference or to determine if the equipment in the system is performing properly. The movement of rolling stock along an electrified track produces certain EMI events. Transient electromagnetic fields are produced in the signalling system when the train leaves the neutral section of the overhead power line and enters the powered section. These transient EM fields are mainly produced by the engine. The track’s infrastructure system has been tested for EMI events, but this phenomenon affects the surrounding environment as well, up to at least 10 meters from the track. The infrastructure is designed so that the return current from locomotives should go through the running rails, but occasionally the ground acts as a conductor, transmitting current to areas that are distant from the rail. The paper reviews the status of Swedish railways with respect to electromagnetic compatibility. This TREND project is a joint project with 7 FP EU.

The measurement of the performance in the maintenance function has produced large sets of indicators that due to their nature and disparity in criteria and objectives have been grouped in different subsets lately, emphasizing the set of financial indicators. The generation of these indicators demands data collection of high reliability that is only made possible through a model of costs adapted to the special casuistry of the maintenance function, characterized by the occultism of these costs.