A framework for data-driven design in a product innovation process: data analysis and visualisation for model-based decision making
by Alessandro Bertoni; Xin Yi; Claude Baron; Phillippe Esteban; Rob Vingerhoeds
International Journal of Product Development (IJPD), Vol. 24, No. 1, 2020

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.

Online publication date: Tue, 07-Apr-2020

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