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

Alessandro Bertoni, Xin Yi, Claude Baron, Phillippe Esteban and Rob Vingerhoeds

International Journal of Product Development, 2020, vol. 24, issue 1, 68-94

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.

Keywords: data-driven design; product innovation; product value stream; knowledge value stream; decision making; data visualisation; data analysis. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=106464 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpdev:v:24:y:2020:i:1:p:68-94

Access Statistics for this article

More articles in International Journal of Product Development from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().