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

Improving the safety and efficiency of rail yard operations using robotics

textSignificant efforts have been expended by the railroad industry to make operations safer and more efficient through the intelligent use of sensor data. This work proposes to take the technology one step further to use this data for the control of physical systems designed to automate hazardous railroad operations, particularly those that require humans to interact with moving trains. To accomplish this, application specific requirements must be established to design self-contained machine vision and robotic solutions to eliminate the risks associated with existing manual operations. Present-day rail yard operations have been identified as good candidates to begin development. Manual uncoupling, in particular, of rolling stock in classification yards has been investigated. To automate this process, an intelligent robotic system must be able to detect, track, approach, contact, and manipulate constrained objects on equipment in motion. This work presents multiple prototypes capable of autonomously uncoupling full-scale freight cars using feedback from its surrounding environment. Geometric image processing algorithms and machine learning techniques were implemented to accurately identify cylindrical objects in point clouds generated in real-vi time. Unique methods fusing velocity and vision data were developed to synchronize a pair of moving rigid bodies in real-time. Multiple custom end-effectors with in-built compliance and fault tolerance were designed, fabricated, and tested for grasping and manipulating cylindrical objects. Finally, an event-driven robotic control application was developed to safely and reliably uncouple freight cars using data from 3D cameras, velocity sensors, force/torque transducers, and intelligent end-effector tooling. Experimental results in a lab setting confirm that modern robotic and sensing hardware can be used to reliably separate pairs of rolling stock up to two miles per hour. Additionally, subcomponents of the autonomous pin-pulling system (APPS) were designed to be modular to the point where they could be used to automate other hazardous, labor-intensive tasks found in U.S. classification yards. Overall, this work supports the deployment of autonomous robotic systems in semi-unstructured yard environments to increase the safety and efficiency of rail operations.Mechanical Engineerin

A function allocation framework for the automation of railway maintenance practices

The railway industry has seen significant innovation in intelligent maintenance systems leading to improvements in efficiency and reliability. However, ongoing challenges such as intensity of labour, hazardous environments, and operational inefficiency necessitate advancement in the deployment of Robotic and Autonomous Systems (RAS). Successful implementation of RAS in a railway context requires a comprehensive function allocation process. This thesis presents a novel function allocation framework for systematic task analysis and allocation. The framework includes comprehensive multi-stage evaluation criteria such as technical feasibility, overall system performance, and cost impact. Function allocation for each identified subtask is realised in an iterative manner to reach a final system design, and the structure and elements of the framework are supported by rigorous derivations and practical examples. The proposed framework has been successfully applied and thoroughly demonstrated through case studies based around the maintenance activities of wheelsets. The case studies demonstrate that the proposed framework is capable of providing guidance in system design at the preliminary stages of the introduction of automation into railway maintenance systems; also, can help to re-evaluate an already implemented system and thus propose guidance on whether the current allocation can be optimised

A review on the prospects of mobile manipulators for smart maintenance of railway track

Inspection and repair interventions play vital roles in the asset management of railways. Autonomous mobile manipulators possess considerable potential to replace humans in many hazardous railway track maintenance tasks with high efficiency. This paper investigates the prospects of the use of mobile manipulators in track maintenance tasks. The current state of railway track inspection and repair technologies is initially reviewed, revealing that very few mobile manipulators are in the railways. Of note, the technologies are analytically scrutinized to ascertain advantages, unique capabilities, and potential use in the deployment of mobile manipulators for inspection and repair tasks across various industries. Most mobile manipulators in maintenance use ground robots, while other applications use aerial, underwater, or space robots. Power transmission lines, the nuclear industry, and space are the most extensive application areas. Clearly, the railways infrastructure managers can benefit from the adaptation of best practices from these diversified designs and their broad deployment, leading to enhanced human safety and optimized asset digitalization. A case study is presented to show the potential use of mobile manipulators in railway track maintenance tasks. Moreover, the benefits of the mobile manipulator are discussed based on previous research. Finally, challenges and requirements are reviewed to provide insights into future research

A literature review of Artificial Intelligence applications in railway systems

Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a large number of domains, including railways. In this paper, we present a systematic literature review of the current state-of-the-art of AI in railway transport. In particular, we analysed and discussed papers from a holistic railway perspective, covering sub-domains such as maintenance and inspection, planning and management, safety and security, autonomous driving and control, revenue management, transport policy, and passenger mobility. This review makes an initial step towards shaping the role of AI in future railways and provides a summary of the current focuses of AI research connected to rail transport. We reviewed about 139 scientific papers covering the period from 2010 to December 2020. We found that the major research efforts have been put in AI for rail maintenance and inspection, while very limited or no research has been found on AI for rail transport policy and revenue management. The remaining sub-domains received mild to moderate attention. AI applications are promising and tend to act as a game-changer in tackling multiple railway challenges. However, at the moment, AI research in railways is still mostly at its early stages. Future research can be expected towards developing advanced combined AI applications (e.g. with optimization), using AI in decision making, dealing with uncertainty and tackling newly rising cybersecurity challenges

Economic and Technical Feasibility of a Robotic Autonomous System for Train Fluid Servicing

Rail traffic in passenger miles is projected to increase by 100% over the next 30 years, which presents a considerable challenge for the current infrastructure to perform the regular fluid servicing tasks. Developing robotic autonomous systems for train fluid servicing is a prospect for which no solutions currently exist. Therefore, the economic and technical feasibility of a robotic autonomous system (RAS) to perform several key fluid servicing tasks on passenger train vehicles is investigated. The fluid servicing tasks chosen include those that to a significant degree are repetitive or hazardous for humans to perform, and therefore if performed by a RAS will release service personnel to focus on more suitable tasks. The economic and technical cases presented strongly support the use of a RAS for fluid servicing of trains. Generally available RAS technology has reached a state of development capable of delivering what is required once reliable couplings and fluid hose technologies have been developed for this application. Overall, the findings are that fluid servicing capacity will at least double for around 15% of the cost of an equivalent manual servicing facility, which represents a substantially attractive business case. There will be modest technical challenges to be overcome that will add unknown cost elements such as modifications to vehicle fluid ports for RAS compatibility, and development of long power hoses

An internet of things enabled system for real-time monitoring and predictive maintenance of railway infrastructure

The railway industry plays a pivotal role in the socioeconomic landscape of many countries. However, its operation poses considerable challenges in terms of safety, environmental impact, and the intricacies of intertwined technical and social structures. Addressing these challenges necessitates the adoption of innovative approaches and advanced technologies. This doctoral research delves into the potential of the Internet of Things (IoT) as an enabler for railway infrastructure monitoring and predictive maintenance, aiming to enhance reliability, efficiency, and safety within the industry. Rooted in a pragmatic modelist philosophical stance, this thesis employs an exploratory sequential mixed-method approach incorporating qualitative and quantitative methodologies. The research process involves engaging with key stakeholders to gain insights into the challenges faced in railway maintenance and the opportunities presented by IoT implementation. Following this, an IoT system is developed, and a comprehensive value-creation framework is proposed for its effective implementation within the railway sector. The findings of this investigation underscore the transformative potential of IoT integration in railway infrastructure monitoring, yielding significant improvements in maintenance processes, safety, and operational efficiency. Furthermore, this doctoral research provides a foundation for future innovation and adaptation in the railway industry, contributing to its ongoing evolution and resilience in an ever-changing technological landscape

Appraisal Of Mass Production Costs For Wave Energy Devices

The objective of this report is to express opinions on the order of possible costs obtainable by adopting a mass production approach to the construction of wave energy devices. From our investigations we believe the following points need to be emphasised. it is important to understand how a "cost" is derived and the relationship of the various elements within the total the designs will have to reconcile the best shape for energy absorption with less efficient but cheaper designs for production ultimately the structural cost of a device is the product of two elements: the mass in tonnes the manufacturing cost in £ per tonne The design development must aim to optimise this product to achieve the minimum cost. the eventual choice of the best device and material will need to consider all the factors in total cost. From the manufacturing point of view the key ratio which needs to be monitored is of course the cost/kw. For a device in a particular material this ratio is derived from the mass/output (tonnes/kw) and the cost/tonne (£/tonne) strategic planning will be required of both the manufacturing methods and facilities to suit the device design, again with particular attention to cost minimisation risk assessment should be included to see the effect of variances with the aim of reducing possible excesses cost reduction studies will be required during the detail design development stage and will be most successful if 'value analysis' type methods are used and emphasis placed on an iterative approach attacking the cost of all elements until a minimum figure is reached. As an example, prestressing materials make up half the material cost of the concrete Raft and are therefore a suitable target for cost reduction. This comment is relevant to all sections of the wave energy programme since the goal must be to find the minimum cost of power generation. When design and manufacturing methods can be reconciled, then significant savings in mass production costs in steel are possible. The concrete designs appear to have a reduced potential because of their size and jointing problems. We suggest that attention to manufacturing and launch out cost should be an ongoing activity once the conceptual design has been resolved. This should clarify design development programmes and by imposing disciplines prevent abort i ve development of non-productive ideas