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A framework for data-driven design in a product innovation process: data analysis and visualisation for model-based decision making

Abstract : The paper presents a four-layer framework for the application of data-driven design in a product innovation process. The framework builds on the Knowledge Value Stream and on the Product Value Streams of a product innovation process and indicates how data-driven activities shall be structured and organised in relation to the different phases of a model-based decision process. Visualisation is proposed as a communication enabler at the top of the framework to overcome the comprehensibility barrier between data science and engineering design models. The framework is implemented in the case study of a construction equipment encompassing the analysis of operational machine data and the experimentation of suitable visualisation techniques. Ultimately, a list of challenges for the implementation of data-driven design is presented, and the capability of the framework to support the transition toward data-driven design is discussed in relation to the emergence of product-service systems solutions.
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https://hal.laas.fr/hal-03004347
Contributor : Xin Yi <>
Submitted on : Friday, November 13, 2020 - 3:53:20 PM
Last modification on : Wednesday, June 9, 2021 - 10:00:25 AM

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Alessandro Bertoni, Xin Yi, Claude Baron, Philippe Esteban, Rob Vingerhoeds. A framework for data-driven design in a product innovation process: data analysis and visualisation for model-based decision making. International Journal of Product Development, Inderscience, 2020, 24 (1), pp.68-94. ⟨10.1504/IJPD.2020.106464⟩. ⟨hal-03004347⟩

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