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DESCRIPTIVE ATTRIBUTES OF ANALYSIS USE CASES IN THE DATA-DRIVEN VALIDATION OF ELEMENTS IN THE SYSTEM OF OBJECTIVES

Published online by Cambridge University Press:  19 June 2023

Steffen Wagenmann ,
Felicia Weidinger ,
Moritz Schöck ,
Albert Albers  and
Nikola Bursac
Steffen Wagenmann*
Affiliation:
TRUMPF Machine Tools SE+Co.KG; IPEK, Karlsruher Institute of Technology;
Felicia Weidinger
Affiliation:
TRUMPF Machine Tools SE+Co.KG;
Moritz Schöck
Affiliation:
IPEK, Karlsruher Institute of Technology;
Albert Albers
Affiliation:
IPEK, Karlsruher Institute of Technology;
Nikola Bursac
Affiliation:
Technical University of Hamburg
*
Wagenmann, Steffen, TRUMPF Machine Tools SE+Co.KG, Germany, steffen.wagenmann@trumpf.com

Abstract

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Usage data of reference systems can be analyzed in the development process for the validation of system elements. The process model for data-driven validation of elements in the system of objectives aids developers in performing such data analyses. The conducted studies show that the basis for an efficient analysis process is a common understanding of the system and the goal of the analysis. Therefore, a template was derived over the course of case studies describing the elements in the system of objectives. The template covers the three descriptive dimensions general information, technical system and data. It allows a comprehensive description of analysis use cases. On average it takes 11 minutes for developers to aggregate all necessary information and consequently fill out the template. An A/B-Test confirmed the comprehensibility and applicability of the template even for developers of different domain knowledge. Through its contribution to a sustainable knowledge management the template provides an added value for the developers for conducting analysis.

Keywords

Big dataComplexityNew product developmentData-driven development
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1207 - 1216
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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