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MODEL-DRIVEN PRODUCT SERVICE SYSTEMS DESIGN: THE MODEL-DRIVEN DEVELOPMENT AND DECISION SUPPORT (MD3S) APPROACH

Published online by Cambridge University Press:  27 July 2021

Alessandro Bertoni*
Affiliation:
Blekinge Institute of Technology, Department of Mechanical Engineering
Tobias Larsson
Affiliation:
Blekinge Institute of Technology, Department of Mechanical Engineering
Johan Wall
Affiliation:
Blekinge Institute of Technology, Department of Mechanical Engineering
Christian Johansson Askling
Affiliation:
Blekinge Institute of Technology, Department of Mechanical Engineering
*
Bertoni, Alessandro, Blekinge Institute of Technology, Mechanical Engineering, Sweden, [email protected]

Abstract

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The paper presents a Model-Driven approach for Product-Service System (PSS) Design promoting an increased digitalization of the PSS design process based on the combination of data-driven design (DDD) activities and value-driven design (VDD) methods. The approach is the results of an 8-year long research profile named (omitted for blind review) featuring the collaboration between (omitted for blind review) and nine industrial companies, in the field of PSS Design. It combines VDD models and the supporting data-driven activities in the frame of PSS design and aligns with the product value stream and the knowledge value stream in the product innovation process as described by Kennedy et al. (2008). The paper provides a high-level overview of the approach describing the different stages and activities, and provides references to external scientific contributions for more exhaustive descriptions of the research rationale and validity. The approach is meant to ultimately drive the development and implementation of a simulation environment for cross-functional and multi-disciplinary decision making in PSS, named Model-Driven Decision Arena, describe in the concluding part of the paper.

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), 2021. Published by Cambridge University Press

References

Agard, B. and Kusiak, A., (2004). Data-mining-based methodology for the design of product families. International Journal of Production Research, 42(15), pp.29552969. https://doi.org/10.1080/00207540410001691929 https://doi.org/10.1016/S0007-8506(07)62286-0CrossRefGoogle Scholar
Bertoni, A. (2018). Role and challenges of data-driven design in the product innovation process. IFAC-PapersOnLine, 51(11), 11071112. https://doi.org/10.1016/j.ifacol.2018.08.455CrossRefGoogle Scholar
Bertoni, A., & Bertoni, M. (2019). Modeling ‘ilities’ in early Product-Service Systems design. In 11th CIRP Conference on Industrial Product-Service Systems, CIRP IPS2 2019; Zhuhai; China; 29 May 2019 through 31 May 2019 (Vol. 83, pp. 230235). Elsevier. https://doi.org/10.1016/j.procir.2019.03.091CrossRefGoogle Scholar
Bertoni, A., & Bertoni, M. (2019b). Supporting early stage set-based concurrent engineering with Value Driven Design. In Proceedings of the Design Society: International Conference on Engineering Design (Vol. 1, No. 1, pp. 23672376). Cambridge University Press. https://doi.org/10.1017/dsi.2019.243CrossRefGoogle Scholar
Bertoni, A., & Larsson, T. (2017). Data mining in product service systems design: Literature review and research questions. Procedia CIRP, 64, 306311. https://doi.org/10.1016/j.procir.2017.03.131CrossRefGoogle Scholar
Bertoni, A., Bertoni, M., Panarotto, M., Johansson, C. & Larsson, T.C. (2016). Value-driven product service systems development: Methods and industrial applications. CIRP Journal of Manufacturing Science and Technology, Vol. 15, pp. 4255. https://doi.org/10.1016/j.cirpj.2016.04.008CrossRefGoogle Scholar
Bertoni, M., & Bertoni, A. (2019a). Iterative value models generation in the engineering design process. Design Science, 5. https://doi.org/10.1017/dsj.2019.13CrossRefGoogle Scholar
Brown, T. (2008). Design Thinking. Harvard Business Review, (June).Google Scholar
Castagne, S., Curran, R., and Collopy, P. (2009). Implementation of value-driven optimisation for the design of aircraft fuselage panels. International journal of production economics, 117(2), 381388. https://doi.org/10.1016/j.ijpe.2008.12.005CrossRefGoogle Scholar
Cheung, J., Scanlan, J., Wong, J., Forrester, J., Eres, H., Collopy, P., Hollingsworth, P., Wiseall, S. & Briceno, S. (2012). Application of value-driven design to commercial aeroengine systems, Journal of Aircraft, Vol. 49, No. 3, pp. 688702. https://doi.org/10.2514/1.C031319CrossRefGoogle Scholar
Collopy, P. D., & Hollingsworth, P. M. (2011). Value-driven design. Journal of aircraft, 48(3), 749759. https://doi.org/10.2514/1.C000311CrossRefGoogle Scholar
Curran, R., van der Zwan, F., & Ouwehand, A. (2010). Value analysis of engine maintenance scheduling relative to fuel burn and minimal operating costs. In 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference (p. 9145). DOI: https://doi.org/10.2514/6.2010-9145CrossRefGoogle Scholar
Domazet, D.S., Choong, F.N., Sng, D., Ho, N.C. & Lu, S.Y., 1995. Active data-driven design using dynamic product models. CIRP annals, 44(1), pp.109112. https://doi.org/10.1016/S0007-8506(07)62286-0CrossRefGoogle Scholar
Isaksson, O., Larsson, T. C., & Rönnbäck, A. Ö. (2009). Development of product-service systems: challenges and opportunities for the manufacturing firm. Journal of Engineering Design, 20(4), 329348. https://doi.org/10.1080/09544820903152663CrossRefGoogle Scholar
Johansson, C., Hicks, B., Larsson, A. C., & Bertoni, M. (2011). Knowledge maturity as a means to support decision making during product-service systems development projects in the aerospace sector. Project Management Journal, 42(2), 3250. https://doi.org/10.1002/pmj.20218CrossRefGoogle Scholar
Johansson, C., Wall, J., & Panarotto, M. (2017). Maturity of models in a multi-model decision support system. In DS 87–6 Proceedings of the 21st International Conference on Engineering Design (ICED 17) Vol 6: Design Information and Knowledge, Vancouver, Canada, 21-25.08. 2017 (pp. 237246).Google Scholar
Kennedy, M., Harmon, K., & Minnock, E. (2008). Ready, Set, Dominate-Implement Toyota's Set-Based Learning for Developing Products and Nobody Can Catch You. Richmond, VA : Oaklea Press. ISBN: 9781511659659Google Scholar
Kim, H. H. M., Liu, Y., Wang, C. C., & Wang, Y. (2017). Data-driven design (D3). Journal of Mechanical Design, 139(11). https://doi.org/10.1115/1.4035002CrossRefGoogle Scholar
Kimita, K., Yoshimitsu, Y., Shimomura, Y., & Arai, T. (2008, January). A customers’ value model for sustainable service design. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 43291, pp. 7785). https://doi.org/10.1016/j.cirpj.2009.06.003Google Scholar
Kusiak, A. & Smith, M., (2007). Data mining in design of products and production systems. Annual Reviews in Control, 31(1), pp.147156. https://doi.org/10.1016/j.arcontrol.2007.03.003CrossRefGoogle Scholar
Kusiak, A. & Tseng, T.I., (2000). Data mining in engineering design: a case study. In Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia 10.1109/ROBOT.2000.844060CrossRefGoogle Scholar
Lugnet, J., Ericson, Å., & Larsson, T. (2020). Design of Product–Service Systems: Toward an Updated Discourse. Systems, 8(4), 45. https://doi.org/10.3390/systems8040045CrossRefGoogle Scholar
Mahut, F., Daaboul, J., Bricogne, M., & Eynard, B. (2017). Product-Service Systems for servitization of the automotive industry: a literature review. International Journal of Production Research, 55(7), 21022120. https://doi.org/10.1080/00207543.2016.1252864CrossRefGoogle Scholar
McManus, H., Richards, M., Ross, A., & Hastings, D. (2007, September). A framework for incorporating “ilities” in tradespace studies. In AIAA Space 2007 Conference & Exposition (p. 6100). DOI: https://doi.org/10.2514/6.2007-6100CrossRefGoogle Scholar
Norman, W., & MacDonald, C. (2004). Getting to the bottom of “triple bottom line”. Business ethics quarterly, 243262. https://doi.org/10.5840/beq200414211CrossRefGoogle Scholar
Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. (2014). Value proposition design: How to create products and services customers want. John Wiley & Sons. ISBN: 978-971-118-96805-5Google Scholar
Panarotto, M., Bertoni, M., & Johansson, C. (2019). Using models as boundary objects in early design negotiations: analysis and implications for decision support systems. Journal of Design Research, 17(2-4), 214237. https://doi.org/10.1504/JDR.2019.105757CrossRefGoogle Scholar
Pezzotta, G., Sassanelli, C., Pirola, F., Sala, R., Rossi, M., Fotia, S., Koutoupes, A., Terzi, S. & Mourtzis, D., (2018). The Product Service System Lean Design Methodology (PSSLDM). Journal of Manufacturing Technology Management. DOI: 10.1108/JMTM-06-2017-0132.10.1108/JMTM-06-2017-0132CrossRefGoogle Scholar
Rondini, A., Bertoni, M., & Pezzotta, G. (2018). At the origins of Product Service Systems: Supporting the concept assessment with the Engineering Value Assessment method. CIRP Journal of Manufacturing Science and Technology. https://doi.org/10.1016/j.cirpj.2018.08.002CrossRefGoogle Scholar
Sakao, T., & Lindahl, M. (2012). A value based evaluation method for Product/Service System using design information. CIRP annals, 61(1), 5154. https://doi.org/10.1016/j.cirp.2012.03.108CrossRefGoogle Scholar
Sala, R., Bertoni, A., Pirola, F., & Pezzotta, G. (2020, August). The Data-Driven Product-Service Systems Design and Delivery (4DPSS) Methodology. In IFIP International Conference on Advances in Production Management Systems (pp. 314321). Springer, Cham.Google Scholar
Soban, D. S., Price, M. A., & Hollingsworth, P. (2012). Defining a research agenda in Value Driven Design: Questions that need to be asked. Journal of Aerospace Operations, 1(4), 329342. DOI: 10.3233/AOP-120026 10.3233/AOP-120026CrossRefGoogle Scholar
Ullman, D. G. (2002). The Mechanical Design Process. McGraw-Hill 946 Science/Engineering/Math. 947. ISBN-13 : 978-007297574Google Scholar
Ulrich, K. T. & Eppinger, S. D. (2012). Product Design and Development, 5th edn. 948 McGraw-Hill Education. ISBN: 9781260566437Google Scholar
Vallhagen, J., Isaksson, O., Söderberg, R., & Wärmefjord, K. (2013). A framework for producibility and design for manufacturing requirements in a system engineering context. Procedia CIRP, 11, 145150. https://doi.org/10.1016/j.procir.2013.07.041CrossRefGoogle Scholar
Vengadasalam, L., Desai, A., Hollingsworth, P., & Smith, K. (2017). Value-Centric/Driven Design–A Framework. 31st ISTS Open up a New Age of Space Discovery, 1-6.Google Scholar
Wall, J., Bertoni, M., & Larsson, T. (2020). The model-driven decision arena: Augmented decision-making for product-service systems design. Systems, 8(2), 22. https://doi.org/10.3390/systems8020022CrossRefGoogle Scholar
Ware, C. (2005). Visual Queries: The Foundation of Visual Thinking, In: Tergan, SO., Keller, T. (eds) Knowledge and Information Visualization. Lecture Notes in Computer Science, vol 3426. Springer, Berlin, HeidelbergGoogle Scholar