How do principles for human-centred automation apply to disruption management decision support?

Golightly, David; Dadashi, Nastaran

doi:10.1109/icirt.2016.7588725

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…The term Robotic Autonomous System (RAS) is used in this paper to embrace the use of robots within autonomous systems. Human-centred automation 6 is a key aspect of the RAS approach and it takes into account human factors to ensure that the tasks best suited to the human are allocated to the human, and the tasks best suited to automating are allocated to the RAS. Attributes of RAS that make them of consideration for application in the servicing of train fluids are in broad terms:…”

Section: Introductionmentioning

confidence: 99%

Economic and technical feasibility of a robotic autonomous system for train fluid servicing

Atherton

Hill

Harrison

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part F:

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Rail traffic in passenger miles [in the UK] 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 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 robotic autonomous system will release service personnel to focus on more suitable tasks. The economic and technical cases presented strongly support the use of a robotic autonomous system for fluid servicing of trains. Generally available robotic autonomous system 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 robotic autonomous system compatibility and development of long power hoses.

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Section: Introductionmentioning

confidence: 99%

Economic and technical feasibility of a robotic autonomous system for train fluid servicing

Atherton

Hill

Harrison

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part F:

View full text Add to dashboard Cite

show abstract

A cross-sector analysis of human and organisational factors in the deployment of data-driven predictive maintenance

Golightly

Kefalidou

Sharples

2017

Inf Syst E-Bus Manage

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Domains such as utilities, power generation, manufacturing and transport are increasingly turning to data-driven tools for management and maintenance of key assets. Whole ecosystems of sensors and analytical tools can provide complex, predictive views of network asset performance. Much research in this area has looked at the technology to provide both sensing and analysis tools. The reality in the field, however, is that the deployment of these technologies can be problematic due to user issues, such as interpretation of data or embedding within processes, and organisational issues, such as business change to gain value from asset analysis. 13 experts from the field of remote condition monitoring, asset management and predictive analytics across multiple sectors were interviewed to ascertain their experience of supplying data-driven applications. The results of these interviews are summarised as a framework based on a predictive maintenance project lifecycle covering project motivations and conception, design and development, and operation. These results identified critical themes for success around having a target-or decision-led, rather than data-led, approach to design; long-term resourcing of the deployment; the complexity of supply chains to provide data-driven solutions and the need to maintain knowledge across the supply chain; the importance of fostering technical competency in end-user organisations; and the importance of a maintenance-driven strategy in the deployment of data-driven asset management. Emerging from these themes are recommendations related to culture, delivery process, resourcing, supply chain collaboration and industry-wide cooperation.

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How do principles for human-centred automation apply to disruption management decision support?

Cited by 2 publications

References 22 publications

Economic and technical feasibility of a robotic autonomous system for train fluid servicing

Economic and technical feasibility of a robotic autonomous system for train fluid servicing

A cross-sector analysis of human and organisational factors in the deployment of data-driven predictive maintenance

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