A software architecture for autonomous maintenance scheduling: Scenarios for UK and European Rail

A new era of automation in rail has begun offering developments in the operation and maintenance of industry standard systems. This article documents the development of an architecture and range of scenarios for an autonomous system for rail maintenance planning and scheduling. The Unified Modelling Language (UML) has been utilized to visualize and validate the design of the prototype. A model for information exchange between prototype components and related maintenance planning systems is proposed in this article. Putting forward an architecture and set of usage mode scenarios for the proposed system, this article outlines and validates a viable platform for autonomous planning and scheduling in rail

An intelligent framework and prototype for autonomous maintenance planning in the rail industry

This paper details the development of the AUTONOM project, a project that aims to provide an enterprise system tailored to the planning needs of the rail industry. AUTONOM extends research in novel sensing, scheduling, and decision-making strategies customised for the automated planning of maintenance activities within the rail industry. This paper sets out a framework and software prototype and details the current progress of the project. In the continuation of the AUTONOM project it is anticipated that the combination of techniques brought together in this work will be capable of addressing a wider range of problem types, offered by Network rail and organisations in different industries

Data fusion strategy for precise vehicle location for intelligent self-aware maintenance systems

Abstract— Nowadays careful measurement applications are handed over to Wired and Wireless Sensor Network. Taking the scenario of train location as an example, this would lead to an increase in uncertainty about position related to sensors with long acquisition times like Balises, RFID and Transponders along the track. We take into account the data without any synchronization protocols, for increase the accuracy and reduce the uncertainty after the data fusion algorithms. The case studies, we have analysed, derived from the needs of the project partners: train localization, head of an auger in the drilling sector localization and the location of containers of radioactive material waste in a reprocessing nuclear plant. They have the necessity to plan the maintenance operations of their infrastructure basing through architecture that taking input from the sensors, which are localization and diagnosis, maps and cost, to optimize the cost effectiveness and reduce the time of operation

A review of key planning and scheduling in the rail industry in Europe and UK

Planning and scheduling activities within the rail industry have benefited from developments in computer-based simulation and modelling techniques over the last 25 years. Increasingly, the use of computational intelligence in such tasks is featuring more heavily in research publications. This paper examines a number of common rail-based planning and scheduling activities and how they benefit from five broad technology approaches. Summary tables of papers are provided relating to rail planning and scheduling activities and to the use of expert and decision systems in the rail industry.EPSR

Precise vehicle location as a fundamental parameter for intelligent selfaware rail-track maintenance systems

The rail industry in the UK is undergoing substantial changes in response to a modernisation vision for 2040. Development and implementation of these will lead to a highly automated and safe railway. Real-time regulation of traffic will optimise the performance of the network, with trains running in succession within an adjacent movable safety zone. Critically, maintenance will use intelligent trainborne and track-based systems. These will provide accurate and timely information for condition based intervention at precise track locations, reducing possession downtime and minimising the presence of workers in operating railways. Clearly, precise knowledge of trains’ real-time location is of paramount importance. The positional accuracy demand of the future railway is less than 2m. A critical consideration of this requirement is the capability to resolve train occupancy in adjacent tracks, with the highest degree of confidence. A finer resolution is required for locating faults such as damage or missing parts, precisely. Location of trains currently relies on track signalling technology. However, these systems mostly provide an indication of the presence of trains within discrete track sections. The standard Global Navigation Satellite Systems (GNSS), cannot precisely and reliably resolve location as required either. Within the context of the needs of the future railway, state of the art location technologies and systems were reviewed and critiqued. It was found that no current technology is able to resolve location as required. Uncertainty is a significant factor. A new integrated approach employing complimentary technologies and more efficient data fusion process, can potentially offer a more accurate and robust solution. Data fusion architectures enabling intelligent self-aware rail-track maintenance systems are proposed

Developing system models to help Great Britain's railways embrace innovative technologies with confidence

Railways are under pressure to become more efficient and cut their costs; innovation has a part to play in achieving these goals. The railway is, however, a complex and closely coupled system, making it difficult in the early stages of development, to be clear what the system-wide impact of innovation will be. The research covered in this paper stems from the idea that computer-based models of existing systems can help overcome this problem, by providing a baseline framework against which the impact of innovation can be identified. The paper describes development of a repeatable modelling methodology, which elicits\ud objective system data from Railway Group Standards and integrates it using CORE®, a powerful system modelling tool, to create system models. The ability of such models to help identify impacts is verified, using as an example the introduction of RailBAM (a new technology that acoustically monitors the health of rolling stock axle bearings) into the existing hot axle bearing detection system

AWARENESS AND ADOPTION OF INTELLIGENT RAILWAY TRANSPORT SYSTEM IN ZIMBABWE

The study seeks to investigate the awareness and adoption of modern technologies which are collectively called (IRTS) Intelligent Railway Transport Systems by the NRZ (National railways of Zimbabwe) of Zimbabwe. Adoption of these technologies are on an increasing trend in developed and developing countries, installation and implementation of a railway system called RailTracker in Tanzania has improved railway services in that country, in Uganda and Kenya the Rift Valley Railway (RVR) has introduced GPS technology to track trains. In India a system is used to detect defects in rolling stock while they are on the run. Where these systems have been implemented, they have significantly improved the efficiency, safety and quality of service of railway operations. In Zimbabwe the rail network is an important transport infrastructure enabling movement of goods and passengers. Primary research was carried out using questionnaires and semi structured interviews, data was collected from 67 participants comprising Engineers, Technicians, Train Drivers and Station Managers. 98% of the technical participants indicated that they were aware of IRTS however the adoption of the systems by the NRZ is at 0%. 100% of the Managers indicated that they were aware of IRTS and the company is willing to adopt them but currently no system has been installed Secondary research was conducted to identify and study similar projects elsewhere, their success as well as the difficulties encountered during their implementation. Secondary data was collected from books and the Internet. Article visualizations

Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense