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In competition with other modes of transport, rail freight transport is looking for solutions to become more attractive. Short-term success can be achieved through the data-driven optimization of operations and maintenance as well as the application of novel strategies such as prescriptive maintenance. After introducing the concept of prescriptive maintenance, this paper aims to prove that vehicle-focused applications of this approach indeed have the potential to increase attractiveness. However, even greater advantages can be activated if data from the horizontal network of the vehicle is available. Drawing on the state of the art in research and technology in the field of cyber-physical systems (CPS) as well as digital twins and shadows, our work serves to design a system of systems for the horizontal interconnection of a rail vehicle and to conceptualize a draft for a digital twin of a locomotive.
Rare event simulation to optimise maintenance intervals of safety critical redundant subsystems
(2018)
For smaller railway operators or those with a diverse fleet, it can be difficult to collect sufficient data to improve maintenance programs. At the same time, new rules such as entity in charge of maintenance – ECM – regulations impose an additional workload by requiring a dedicated maintenance management system and specific reports. The RailCrowd platform sets out to facilitate compliance with ECM and similar regulations while at the same time pooling anonymised fleet data across operators to form virtual fleets, providing greater data insights.
Sensor positioning and thermal model for condition monitoring of pressure gas reservoirs in vehicles
(2018)
This work demonstrates how the interaction between particle image velocimetry (PIV) and robotics can massively increase measurement efficiency. The interdisciplinary approach is shown using the complex example of an automated, large scale, industrial environment: a typical automotive wind tunnel application. Both the high degree of flexibility in choosing the measurement region and the complete automation of stereo PIV measurements are presented. The setup consists of a combination of three robots, individually used as a 6D traversing unit for the laser illumination system as well as for each of the two cameras. Synchronised movements in the same reference frame are realised through a master-slave setup with a single interface to the user. By integrating the interface into the standard wind tunnel management system, a single measurement plane or a predefined sequence of several planes can be requested through a single trigger event, providing the resulting vector fields within minutes.
In this paper, a brief overview on the demands of large scale industrial PIV and the existing solutions is given. Afterwards, the concept of RoboPIV is introduced as a new approach. In a first step, the usability of a selection of commercially available robot arms is analysed. The challenges of pose uncertainty and importance of absolute accuracy are demonstrated through comparative measurements, explaining the individual pros and cons of the analysed systems. Subsequently, the advantage of integrating RoboPIV directly into the existing wind tunnel management system is shown on basis of a typical measurement sequence. In a final step, a practical measurement procedure, including post-processing, is given by using real data and results. Ultimately, the benefits of high automation are demonstrated, leading to a drastic reduction in necessary measurement time compared to non-automated systems, thus massively increasing the efficiency of PIV measurements.
The rail business is challenged by long product life cycles and a broad spectrum of assembly groups and single parts. When spare part obsolescence occurs, quick solutions are needed. A reproduction of obsolete parts is often connected to long waiting times and minimum lot quantities that need to be purchased and stored. Spare part storage is therefore challenged by growing stocks, bound capital and issues of part ageing. A possible solution could be a virtual storage of spare parts which will be 3D printed through additive manufacturing technologies in case of sudden demand. As mechanical properties of additive manufactured parts are neither guaranteed by machine manufacturers nor by service providers, the utilization of this relatively young technology is impeded and research is required to address these issues. This paper presents an examination of mechanical properties of specimens manufactured from stainless steel through the selective laser melting (SLM) process. The specimens were produced in multiple batches. This paper interrogates the question if the test results follow a normal distribution pattern and if mechanical property predictions can be made. The results will be put opposite existing threshold values provided as the industrial standard. Furthermore, probability predictions will be made in order to examine the potential of the SLM process to maintain state-of-the-art mechanical property requirements.
The potential of SMART climbing robot combined with a weatherproof cabin for rotor blade maintenance
(2016)