Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-25T22:16:34.489Z Has data issue: false hasContentIssue false

DATA ANALYSIS METHOD SUPPORTING CAUSE AND EFFECT STUDIES IN PRODUCT-SERVICE SYSTEM DEVELOPMENT

Published online by Cambridge University Press:  11 June 2020

J. Wall*
Affiliation:
Blekinge Institute of Technology, Sweden
O. K. Aeddula
Affiliation:
Blekinge Institute of Technology, Sweden
T. Larsson
Affiliation:
Blekinge Institute of Technology, Sweden

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

A data analysis method aiming to support cause and effect analysis in design exploration studies is presented. The method clusters and aggregates effects of multiple design variables based on the structural hierarchy of the evaluated system. The resulting dataset is intended as input to a visualization construct based on colour-coding CAD models. The proposed method is exemplified in a case study showing that the predictive capability of the created, clustered, dataset is comparable to the original, unmodified, one.

Type
Article
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), 2020. Published by Cambridge University Press

References

Allen, M.P. (1997), Understanding regression analysis, Plenum Press, New York. https://doi.org/10.1007/b102242Google Scholar
Benyon, D. and Mival, O. (2015), “Blended Spaces for Collaboration”, Computer Supported Cooperative Work (CSCW), Vol. 24, pp. 223249. https://doi.org/10.1007/s10606-015-9223-8CrossRefGoogle Scholar
Bertoni, A. (2013), “Analyzing Product-Service Systems conceptual design: The effect of color-coded 3D representation”, Design Studies, Vol. 34 No. 6, pp. 763793. https://doi.org/10.1016/j.destud.2013.02.003Google Scholar
Bertoni, M. et al. (2019) “Life cycle simulation to support cross-disciplinary decision making in early PSS design”, Procedia, ISSN 2212 - 8271, EISSN 83, Procedia CIRP, Elsevier. https://doi.org/10.1016/j.procir.2019.03.138Google Scholar
Boulesteix, A.-L. and Strimmer, K. (2006), “Partial least squares: a versatile tool for the analysis of high-dimensional genomic data”, Briefings in Bioinformatics, Vol. 8 No. 1, pp. 3244. https://doi.org/10.1093/bib/bbl016CrossRefGoogle ScholarPubMed
Bring, J. (1994), “How to Standardize Regression Coefficients”, The American Statistician, Vol. 48 No. 3, pp. 209213. https://doi.org/10.1080/00031305.1994.10476059Google Scholar
Collopy, P.D. and Hollingsworth, P.M. (2011), “Value-driven design”, Journal of Aircraft, Vol. 48 No. 3, pp. 749759. https://doi.org/10.2514/1.C000311CrossRefGoogle Scholar
Crnkovic, I. and Larsson, M. (2004), “Classification of quality attributes for predictability in component-based systems”, Proc. of Workshop on Architecting Dependable System, IEEEGoogle Scholar
Devore, J.L. (2012), Probability and statistics for engineering and the sciences, 8th ed., Brooks/Cole, Cengage Learning, Australia.Google Scholar
Geromin, A. et al. (2018), “CAD modelling based on knowledge synthesis for design rational”, Procedia CIRP, Vol. 70, pp. 156161. https://doi.org/10.1016/j.procir.2018.01.008.Google Scholar
Giunta, A.A., Wojtkiewicz, S.F. and Eldred, M.S. (2003), “Oveview of modern design of experiment methods for computational simulation”, 41st Aerospace Sciences Meeting and Exhibit, Reno, Nevada. https://doi.org/10.2514/6.2003-649Google Scholar
Grunert, K.G. (1989), “Attributes, attribute values and their characteristics: A unifying approach and an example involving a complex household investment”, In Journal of Economic Psychology, Vol. 10 No. 2, pp. 229251. https://doi.org/10.1016/0167-4870(89)90021-4CrossRefGoogle Scholar
Ladyman, J., Lambert, J. and Wiesner, K. (2013), “What is a complex system?”, European Journal for Philosophy of Science, Vol. 3 No. 1, pp. 3367. https://dx.doi.org/10.1007/s13194-012-0056-8.CrossRefGoogle Scholar
Larsson, A. (2003) “Making sense of collaboration: the challenge of thinking together in global design teams”, in. ACM Press, p. 153. https://dx.doi.org/10.1145/958160.958184.CrossRefGoogle Scholar
Loretan, M.S. and Kurz-Kim, J.-R. (2007), “A note on the coefficient of determination in regression models with infinite-variance variables”, Discussion Paper Series 1: Economic Studies. Available at: https://ideas.repec.org/p/zbw/bubdp1/5574.html (Accessed: 1 November 2019).CrossRefGoogle Scholar
McComb, C., Cagan, J. and Kotovsky, K. (2015), “Rolling with the punches: An examination of team performance in a design task subject to drastic changes”, Design Studies, Vol. 36, pp. 99121. https://doi.org/10.1016/j.destud.2014.10.001CrossRefGoogle Scholar
Murakami, Y. (2016), “Linking knowledge absorption and transmission toward innovation in R & D organizations”, in Proceedings of the 17th European Conference on Knowledge Management, ECKM 2016. vol. 2016-January, Academic Conferences Limited, pp. 667675.Google Scholar
Nieminen, M.P., Tyllinen, M. and Runonen, M. (2013), “Digital war room for design”, Proceedings of the 15th international conference on Human Interface and the Management of Information: information and interaction for learning, culture, collaboration and business, July 21-26, Las Vegas, NV. https://doi.org/10.1007/978-3-642-39226-9_39CrossRefGoogle Scholar
Ostad-Ahmad-Ghorabi, H., Collado-Ruiz, D. and Wimmer, W. (2009), “Towards Integrating LCA into CAD”, Proceedings of ICED 09, the 17th International Conference on Engineering Design, Vol. 7, Design for X / Design to X, Palo Alto, CA, USA, pp. 301310.Google Scholar
Pirouz, D.M. (2006), “An Overview of Partial Least Squares”, SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1631359Google Scholar
Price, M. et al. (2012), “A novel method to enable trade-offs across the whole product life of an aircraft using value driven design”, Journal of Aerospace Operations, Vol. 1 No. 4, pp. 359375. https://doi.org/10.3233/AOP-120028CrossRefGoogle Scholar
Rhodes, D.H. and Ross, A.M. (2016), “A vision for human-model interaction in interactive model-centric systems engineering”, In 26th Annual INCOSE International Symposium, Edinburgh. Scotland. https://doi.org/10.1002/inst.12162CrossRefGoogle Scholar
Rännar, S. et al. (1995), “A PLS kernel algorithm for data sets with many variables and few objects. Part II: Cross-validation, missing data and examples”, Journal of Chemometrics, Vol. 9 No. 6, pp. 459470. https://doi.org/10.1002/cem.1180090604CrossRefGoogle Scholar
Sundin, E. et al. (2009), “Challenges for Industrial Product/Service Systems - Experiences from a learning network of large companies”, In: Industrial product- service systems (IPS2): proceedings of the 1st CIRP IPS2 Conference, 01 - 02 April, Cranfield University, UK.Google Scholar
Thomke, S. and Fujimoto, T. (2000), “The effect of ”Front-Loading“ problem-solving on product development performance”, Journal of Product Innovation Management, Vol. 17 No. 2, pp. 128142. https://doi.org/10.1016/S0737-6782(99)00031-4CrossRefGoogle Scholar
Wall, J., Bertoni, M., and Larsson, T. (2018), “A model-driven decision arena: Augmenting decision making in early design”, Proceedings of NordDesign 2018, August 16th-18th Linköping.Google Scholar
Wang, L. et al. (2002), “Collaborative conceptual design—state of the art and future trends”, Computer-Aided Design, Vol. 34 No. 13, pp. 981996. https://doi.org/10.1016/S0010-4485(01)00157-9CrossRefGoogle Scholar
Ware, C. (2005), “Visual Queries: The Foundation of Visual Thinking”, In: Tergan, S.O. and Keller, T. (eds), Knowledge and Information Visualization. Lecture Notes in Computer Science, Vol. 3426, Springer, Berlin, Heidelberg. https://doi.org/10.1007/11510154_2Google Scholar
White, D.D. et al. (2015), “Water management decision makers’ evaluations of uncertainty in a decision support system: the case of WaterSim in the Decision Theater”, Journal of Environmental Planning and Management, Vol. 58 No. 4, pp. 616630, https://doi.org/10.1080/09640568.2013.875892CrossRefGoogle Scholar
Yip, P.S.L. and Tsang, E.W.K. (2007), “Interpreting dummy variables and their interaction effects in strategy research”, Strategic Organization, Vol. 5 No. 1, pp. 1330. https://doi.org/10.1177/1476127006073512.Google Scholar