Success Factors for the Validation of Requirements for New Product Generations – A Case Study on Using Field Gathered Data

DS 116: Proceedings of the DESIGN2022 17th International Design Conference

Year: 2022
Editor: Mario Štorga, Stanko Škec, Tomislav Martinec, Dorian Marjanović
Author: Steffen Wagenmann, Nikola Bursac, Simon Rapp, Albert Albers
Series: DESIGN
Institution: Karlsruhe Institute of Technology, Germany
Section: Artificial Intelligence and Data-Driven Design
Page(s): 1805-1814
DOI number:
ISSN: 2732-527X (Online)


This paper investigates which activities and success factors can be identified for the data-driven validation of functional requirements. For this purpose, a case study is conducted at a machine tool manufacturer. To validate functional requirements by analyzing data of reference products, these activities must be performed iteratively: basic work, interdisciplinary work, programming and check results. For the successful execution of data-driven validation, the success factors: data origin, acceptance, data quality, knowledge about data and combination of domain knowledge must be considered.

Keywords: industry 4.0, digital twin, product generation engineering (PGE), decision making, internet of things (IoT)

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