A function allocation framework for the automation of railway maintenance practices

Yang, Fan (2022). A function allocation framework for the automation of railway maintenance practices. University of Birmingham. Ph.D.

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Abstract

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.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):