Clustering Technique for DSMs

Authors

  • Florian G. H. Behncke Institute of Product Development, Technische Universität München, Germany Germany
  • Doris Maurer Institute of Product Development, Technische Universität München, Germany Germany
  • Lukas Schrenk Institute of Product Development, Technische Universität München, Germany Germany
  • Danilo M. Schmidt Institute of Product Development, Technische Universität München, Germany Germany
  • Udo Lindemann Institute of Product Development, Technische Universität München, Germany Germany

Keywords:

Clustering, Cluster Configuration, Solution Space Exploration

Abstract

This paper provides a clustering technique (CT) for Design-Structure-Matrices (DSMs) that explore the entire solution space of cluster configurations (CCs) for a given system. Therefore the paper gives an overview of established CTs for exclusive clusters as basis for the development of an alternative CT that generates all possible CCs. These configurations are assessed against a set of performance metrics, which are selected by the decision makers to determine the quality of the cluster. Through a representation of the CCs in a portfolio according to the values of the performance metrics, decision makers are provided with a ranking of CCs as s support for their decision. Thereby, it is observed that established CTs do not capture the entire solution space of CCs and therefore miss comparable configurations. As a result, decision makers are not necessarily equipped with ideal CCs by established CTs.

Author Biographies

  • Florian G. H. Behncke, Institute of Product Development, Technische Universität München, Germany Germany

    F. G. H. Behncke is a scientific assistant at the Institute of Product Development (Faculty of Mechanical Engineering) at the Technische Universität München, Germany (www.pe.mw.tum.de). He graduated in mechanical engineering in 2010 with a focus on vehicle and production technology. His research is centers on Systems Engineering, Complexity Management, Product Design as well as Supply Chain Management. He dedicates his research career to the synchronization between the product and supply chain design, which manifests in his PhD topic on “Designfor Procurement – Matching between product architecture and supply network design in early phases of product development”.

  • Doris Maurer, Institute of Product Development, Technische Universität München, Germany Germany

    D. Maurer studied Aerospace between 2008 and 2012 at Technische Universität München and finished her degree with Bachelor of Science. Between 2012 and 2014 she continued with the master’s programme Mechanical Engineering and majored in „Flow and Flight Physics“and in „Production Management“. During her master’s programme she started working on complexity management and cluster optimization. On the basis of two examplesshe develops two algorithms which support the thesis that information exchange at a minimum number of critical intersections leads to more robust processes. In the following she worked as scientific assistant at the institute of Product Development dealing with the topic of clustering techniques. She graduated at Technische Universität München with her master’s degree in June 2014. Today she is working as a development engineer in Munich.

  • Lukas Schrenk, Institute of Product Development, Technische Universität München, Germany Germany

    L. E.-M. Schrenk isan Aerospace Technology Student at the Technical University of Munich, currently working on his joined Master Thesis between the Technische Universität München, Germany and the Massachusetts Instituteof Technology (MIT). He is a Student Research Assistant at the Institute of Product Development and works on Complexity Management and Structural Supply Chain Management. The topic of his Bachelor Thesis was the computational configuration of supply chain networks based on a product’s architecture. Thereby a predecessor of the clustering method presented in the paper at hand has been applied to determine and analyze all possible product architecture and supply chain configurations.

  • Danilo M. Schmidt, Institute of Product Development, Technische Universität München, Germany Germany

    D. M. Schmidt was bornin Berlin (Germany) at July 1st 1988. He did his diploma degree in mechanical engineering at Technische Universität München and did his diploma thesis at Tel Aviv University about “Developmentof an Optimization Algorithm for Adaptable Product Architecture Design”. He has graduated in 2012 and since then, he is aresearch assistant and PhD-student at the institute of Product Development at the Technische Universität München. His PhD’stopic is “Increasing Customer Acceptance inPSS-Planning” and he is supervised by Prof. Udo Lindemann. The main research focusare Product-Service Systems, Customer acceptance, decision-making in product planning and decision processes. Other research deals with knowledge management,complexity management and analysis of industrial clusters.

  • Udo Lindemann, Institute of Product Development, Technische Universität München, Germany Germany

    U. Lindemann succeeded Professor Ehrlenspiel in 1995 as head of the Institute of Product Developmentat the Technical Universityof Munich. Within the time since 1995 until today he served as Dean for Study Affairs and as Dean of the Faculty Mechanical Engineering.Today he is a member of the Academic Senate of the Technical University Munich. He is co-publishers of the German journal„Konstruktion“ and co-editor of several international journals. Since the initiation of the Design Society, he has been an active member, from 2007 to 2010 he served as its President. In addition he is an active member of a number of scientific societies and other organisations. 2008 he became a member of the German Academy of Science and Engineering.

References

Berkhin, P. (2006). A Survey of Clustering Data Mining Techniques. In Grouping multidimensional data (pp. 25–71). Berlin: Springer.

Bronstein, I. N., Semendjajew, K. A., Musiol, G., & Mühlig, H. (1999). Taschenbuch der Mathematik. Frankfurt am Main: Harri Deutsch.

Browning, T. R. (2001). Applying the Design Structure Matrix to System Decomposition and Integration Problems: A Review and New Directions. IEEE Transactions on Engineering Management, 48(3), 292–306. doi:10.1109/17.946528

Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. New York: John Wiley & Sons.

Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster Analysis. Chichester: Wiley.

Jain, A. K., & Dubes, R. C. (1988). Algorithms for Clustering Data. New Jersey: Prentice Hall.

Kreimeyer, M. (2009). A Structural Measurement System for Engineering Design Processes. Lehrstuhl Für Produktentwicklung. München: Technische Universität München.

Lance, G. N., & Williams, W. T. (1967). A general theory of classificatory sorting strategies - I. Hierarchical system. Computer Journal, 9, 373–380.

Lindemann, U., Maurer, M., & Braun, T. (2009). Structural Complexity Management - An Approach for the Field of Product Design. Berlin: Springer.

Newman, M. E. J. (2003). The structure and function of complex networks. SIAM Review, 45(2), 167–256.

Pimmler, T. U., & Eppinger, S. D. (1994). Integration analysis of product decompositions. In American Society of Mechanical Engineers, Design Engineering Division (Publication) DE (Vol. 68, pp. 343–351).

Sharman, D. M., & Yassine, A. A. (2004). Characterizing Complex Product Architectures. Systems Engineering, 7(1), 35–60. doi:10.1002/sys.10056

Yassine, A. A. (2010). Multi-domain DSM: Simultaneou optimization of product, process & people DSMs. In 12th International Dependency and Structure Modelling Conference (pp. 319–332). Cambridge, UK.

Downloads

Published

2022-05-20

Issue

Vol. 3 No. 2 (2015): The Journal of Modern Project Management

Section

Articles-JMPM

License

Copyright (c) 2022 Florian G. H. Behncke, Doris Maurer, Lukas Schrenk, Danilo M. Schmidt, Udo Lindemann

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Clustering Technique for DSMs. (2022). The Journal of Modern Project Management, 3(2), 134. https://journalmodernpm.com/manuscript/index.php/jmpm/article/view/205

Similar Articles

31-40 of 52

You may also start an advanced similarity search for this article.