Improving the performance of railway track-switching through the introduction of fault tolerance

In the future, the performance of the railway system must be improved to accommodate increasing passenger volumes and service quality demands. Track switches are a vital part of the rail infrastructure, enabling traffic to take different routes. All modern switch designs have evolved from a design first patented in 1832. However, switches present single points of failure, require frequent and costly maintenance interventions, and restrict network capacity. Fault tolerance is the practice of preventing subsystem faults propagating to whole-system failures. Existing switches are not considered fault tolerant. This thesis describes the development and potential performance of fault-tolerant railway track switching solutions. The work first presents a requirements definition and evaluation framework which can be used to select candidate designs from a range of novel switching solutions. A candidate design with the potential to exceed the performance of existing designs is selected. This design is then modelled to ascertain its practical feasibility alongside potential reliability, availability, maintainability and capacity performance. The design and construction of a laboratory scale demonstrator of the design is described. The modelling results show that the performance of the fault tolerant design may exceed that of traditional switches. Reliability and availability performance increases significantly, whilst capacity gains are present but more marginal without the associated relaxation of rules regarding junction control. However, the work also identifies significant areas of future work before such an approach could be adopted in practice

Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles: Report 5 - Phase 2 Implementation of the Concept Demonstrator

This report describes the second phase of the implementation of the Concept Demonstrator experimental test-bed system containing sensors and processing hardware distributed throughout the structure, which uses multi-agent algorithms to characterize impacts and determine a suitable response to these impacts. This report expands and adds to the report of the first phase implementation. The current status of the system hardware is that all 192 physical cells (32 on each of the 6 hexagonal prism faces) have been constructed, although only four of these presently contain data-acquisition sub-modules to allow them to acquire sensor data. Impact detection.. location and severity have been successfully demonstrated. The software modules for simulating cells and controlling the test-bed are fully operational. although additional functionality will be added over time. The visualization workstation displays additional diagnostic information about the array of cells (both real and simulated) and additional damage information. Local agent algorithms have been developed that demonstrate emergent behavior of the complex multi-agent system, through the formation of impact damage boundaries and impact networks. The system has been shown to operate well for multiple impacts. and to demonstrate robust reconfiguration in the presence of damage to numbers of cells

Smart manufacturing scheduling: A literature review

[EN] Within the scheduling framework, the potential of digital twin (DT) technology, based on virtualisation and intelligent algorithms to simulate and optimise manufacturing, enables an interaction with processes and modifies their course of action in time synchrony in the event of disruptive events. This is a valuable capability for automating scheduling and confers it autonomy. Automatic and autonomous scheduling management can be encouraged by promoting the elimination of disruptions due to the appearance of defects, regardless of their origin. Hence the zero-defect manufacturing (ZDM) management model oriented towards zero-disturbance and zero-disruption objectives has barely been studied. Both strategies combine the optimisation of production processes by implementing DTs and promoting ZDM objectives to facilitate the modelling of automatic and autonomous scheduling systems. In this context, this particular vision of the scheduling process is called smart manufacturing scheduling (SMS). The aim of this paper is to review the existing scientific literature on the scheduling problem that considers the DT technology approach and the ZDM model to achieve self-management and reduce or eliminate the need for human intervention. Specifically, 68 research articles were identified and analysed. The main results of this paper are to: (i) find methodological trends to approach SMS models, where three trends were identified; i.e. using DT technology and the ZDM model, utilising other enabling digital technologies and incorporating inherent SMS capabilities into scheduling; (ii) present the main SMS alignment axes of each methodological trend; (iii) provide a map to classify the literature that comes the closest to the SMS concept; (iv) discuss the main findings and research gaps identified by this study. Finally, managerial implications and opportunities for further research are identified.This work was supported by the Spanish Ministry of Science, Innovation and Universities project entitled 'Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0) ' (RTI2018-101344-B-I00) , the European Union H2020 research and innovation programme with grant agreement No. 825631 "Zero Defect Manufacturing Platform (ZDMP) " and the European Union H2020 research and innovation programme with agreement No. 958205 "In-dustrial Data Services for Quality Control in Smart Manufacturing (i4Q) ".Serrano-Ruiz, JC.; Mula, J.; Poler, R. (2021). Smart manufacturing scheduling: A literature review. Journal of Manufacturing Systems. 61:265-287. https://doi.org/10.1016/j.jmsy.2021.09.0112652876

Smart Deployment of Demonstrators into Successful Commercial Solutions

AbstractProduct or service concepts based on emerging technologies are usually results of research projects, be they performed by academic groups or by research departments of companies. Many times, the prototypes or demonstrators that result from such projects are supposed to evolve into commercial products or services, but – at least in the first stage - there are more focus on proving key features of a technology, or the effectiveness / efficiency / applicability of various concepts or algorithms. However, evolving into commercial products is many times at least as challenging as building the prototypes. In case of software-based projects, this means changes in architecture, a lot of code rewriting and important usability improvements. This paper introduces a software-concept product design algorithm which aims to minimize the effort required in turning a demonstrator into a commercial product. This is done by generating two functionality sets: a pure demonstrator and a pure commercial one, then generating a hybrid functionality set with the corresponding architecture, and then assessing each functionality for the demonstrator and the commercial version in terms of development and improvement effort. Through iterations, in which the original functionality sets are improved, the difference between the two perspectives will be reduced until it gets below a reasonable limit in terms of effort. The paper presents a case study in which the algorithm is applied for planning a software platform for supporting SMEs in their innovation processes

An autonomous rail-road amphibious robotic system for railway maintenance using sensor fusion and mobile manipulator

The current maintenance of railway infrastructure replies heavily on human involvement, requiring possession of the track section during maintenance, resulting in high costs and inefficient execution. This paper proposes an autonomous rail-road amphibious robotic system for railway inspection and maintenance tasks. By virtue of its road and rail-autonomous mobility, it is able to execute the complete maintenance execution flow in multiple phases. The system provides flexible track job location access, low-cost maintenance execution, and reduced track network possession. The payload mobile manipulator and sensor fusion enhance the system's capabilities for multiple types of inspection and repair. The design of a command and control system was guided by a rule-based expert system strategy to enable remote operation of the whole system. The developed demonstrator of a track wheel accompanied unmanned ground vehicle was integrated and demonstrated in both operational and realistic track environments with multiple testing activities of remote operation, navigation, accurate job detection, inspection, and repair, confirming effective job completion and logical human interaction. The proposed method produces an outstanding hardware-software integrated robotic inspection and repair system with a high level of technological readiness for autonomous railway maintenance and intelligent railway asset management

Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles: Report 3 - Design of the Concept Demonstrator

This report provides an outline of the essential features of a Structural Health Monitoring Concept Demonstrator (CD) that will be constructed during the next eight months. It is emphasized that the design cannot be considered to be complete, and that design work will continue in parallel with construction and testing. A major advantage of the modular design is that small modules of the system can be developed, tested and modified before a commitment is made to full system development. The CD is expected to develop and evolve for a number of years after its initial construction. This first stage will, of necessity, be relatively simple and have limited capabilities. Later developments will improve all aspects of the functionality of the system, including sensing, processing, communications, intelligence and response. The report indicates the directions this later development will take

Diagnostic and prognostic analysis tools for monitoring degradation in aged structures

This research addresses the problem of prolonging the life of aged structures of historical value that have already outlived their original designed lives many times. While a lot of research has been carried out in the field of structural monitoring, diagnostics and prognostics for high tech industries, this is not the case for historical aged structures. Currently most maintenance projects for aged structures have focused on the instrumentation and diagnostic techniques required to detect any damage with a certain degree of success. This research project involved the development of diagnostic and prognostic tools to be used for monitoring and predicting the ‘health’ of aged structures. The diagnostic and prognostic tools have been developed for the monitoring of Cutty Sark iron structures as a first application. The concept of canary and parrot sensor devices are developed where canary devices are small, accelerated devices, which will fail according to similar failure mechanisms occurring in an aged structures and parrot devices are designed to fail at the same rate as the structure, thus mimicking the structure. The model-driven prognostic tool uses a Physics-of-Failure (PoF) model to predict remaining life of a structure. It uses a corrosion model based on the decrease in corrosion rate over time to predict remaining life of an aged iron structures. The data-driven diagnostic tool developed uses Mahalanobis Distance analysis to detect anomalies in the behaviour of a structure. Bayesian Network models are then used as a fusion method, integrating remaining life predictions from the model-driven prognostic tool with information of possible anomalies from data-driven diagnostic tool to provide a probability distribution of predicted remaining life. The diagnostics and prognostic tools are validated and tested through demonstration example and experimental tests. This research primarily looks at applying diagnostic and prognostic technologies used in high-tech industries to aged iron structures. In order to achieve this, the model-driven and data-driven techniques commonly used had to be adapted taking into consideration the particular constraints of monitoring and maintaining aged structures. The fusion technique developed is a novel approach for prognostics for aged structures and provides the flexibility often needed for diagnostic and prognostic tools