The Value of Information in Clustering Dense Matrices: When and How to Make Use of Information

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

Year: 2022
Editor: Mario Štorga, Stanko Škec, Tomislav Martinec, Dorian Marjanović
Author: Felix Endress (1,2), Timoleon Kipouros (1), Tina Buker (3), Sandro Wartzack (3), P. John Clarkson (1)
Series: DESIGN
Institution: 1: Department of Engineering, University of Cambridge, United Kingdom; 2: TUM School of Engineering and Design, Technical University of Munich, Germany; 3: Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Section: Design Information and Knowledge
Page(s): 703-712
DOI number: https://doi.org/10.1017/pds.2022.72
ISSN: 2732-527X (Online)

Abstract

Characterising a socio-technical system by its underlying structure is often achieved by cluster analyses and bears potentials for engineering design management. Yet, highly connected systems lack clarity when systematically searching for structures. At two stages in a clustering procedure (pre-processing and post-processing) modelled and external information were used to reduce ambiguity and uncertainty of clustering results. A holistic decision making on 1) which information, 2) when, and 3) how to use is discussed and considered inevitable to reliably cluster highly connected systems.

Keywords: cluster analysis, design structure matrix (DSM), socio-technical systems, dense matrices, design models