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.
data-driven design, product innovation, product value stream, knowledge value stream, decision making, data visualisation, data analysis
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 24, no. 1 (2020): 68-94.