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

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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.

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  1. Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen, 361005, China

    Liang Hou

  2. School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332-0405, USA

    Liang Hou & Roger J. Jiao

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Hou, L., Jiao, R.J. Data-informed inverse design by product usage information: a review, framework and outlook. J Intell Manuf 31, 529–552 (2020). https://doi.org/10.1007/s10845-019-01463-2

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