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.<\/p>\n\n\n\n
Keywords: <\/strong><\/p>\n\n\n\n data-driven design, product innovation, product value stream, knowledge value stream, decision making, data visualisation, data analysis<\/p>\n\n\n\n Citation: <\/strong><\/p>\n\n\n\n Bertoni, Alessandro, Xin Yi, Claude Baron, Phillippe Esteban, and 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<\/em> 24, no. 1 (2020): 68-94. <\/p>\n\n\n\n Download: <\/strong><\/p>\n\n\n\n https:\/\/www.inderscienceonline.com\/doi\/abs\/10.1504\/IJPD.2020.106464<\/a><\/p>\n\n\n\n