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Optimisation in Friction Stir Welding: Modelling, Monitoring and Design

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Optimization in Industry

Part of the book series: Management and Industrial Engineering ((MINEN))

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Abstract

The friction stir welding process involves a highly complex microstructure evolution. This makes it very difficult to derive intricate relationships among operating conditions , in-process variables and characteristics of welds, and utilise the relationships into modelling, monitoring and optimal design of operating conditions . In this research, a heuristic optimisation paradigm Reduced Space Searching Algorithm, combined with soft-computing-based modelling and data analysis techniques, is employed to solve the problem. The research investigates an aluminium alloy AA5083 and includes three facets of research: first, developing a weld quality indicator that can provide a reliable indication of ‘as-welded’ defects for an online monitoring system; second, generating accurate and interpretable prediction models for both internal process attributes and post-weld properties; third, finding optimal operating conditions to enhance welding productivity, process reliability and cost efficiency.

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Author information

Authors and Affiliations

  1. Department of Electronics and Electrical Engineering, Liverpool John Moores University, Liverpool, L33AF, UK

    Qian Zhang

  2. General Engineering Research Institute, Liverpool John Moores University, Liverpool, L33AF, UK

    Xiaoxiao Liu

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  1. Qian Zhang
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  2. Xiaoxiao Liu
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Correspondence to Qian Zhang .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, SRM Institute of Science and Technology, Chennai, India

    Shubhabrata Datta

  2. Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal

    J. Paulo Davim

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Zhang, Q., Liu, X. (2019). Optimisation in Friction Stir Welding: Modelling, Monitoring and Design. In: Datta, S., Davim, J. (eds) Optimization in Industry. Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-01641-8_11

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  • DOI: https://doi.org/10.1007/978-3-030-01641-8_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01640-1

  • Online ISBN: 978-3-030-01641-8

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