Data-informed inverse design by product usage information: a review, framework and outlook

Liang Hou and Roger J. Jiao ()
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Liang Hou: Xiamen University
Roger J. Jiao: Georgia Institute of Technology

Journal of Intelligent Manufacturing, 2020, vol. 31, issue 3, No 1, 529-552

Abstract: Abstract A significant body of knowledge exists on inverse problems and extensive research has been conducted on data-driven design in the past decade. This paper provides a comprehensive review of the state-of-the-art methods and practice reported in the literature dealing with many different aspects of data-informed inverse design. By reviewing the origins and common practice of inverse problems in engineering design, the paper presents a closed-loop decision framework of product usage data-informed inverse design. Specifically reviewed areas of focus include data-informed inverse requirement analysis by user generated content, data-informed inverse conceptual design for product innovation, data-informed inverse embodiment design for product families and product platforming, data-informed inverse analysis and optimization in detailed design, along with prevailing techniques for product usage data collection and analytics. The paper also discusses the challenges of data-informed inverse design and the prospects for future research.

Keywords: Inverse design; Product usage information; Data-informed design; Data analytics; Cyber-physical systems (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10845-019-01463-2

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