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Exploration of the Digital Twin for Prototyping the Product-Service System Design in a Bus Manufacturing Company
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)ORCID iD: 0000-0003-3711-264X
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)ORCID iD: 0000-0002-9662-4576
2024 (English)In: Design, User Experience,and Usability / [ed] Aaron Marcus, Elizabeth Rosenzweig, Marcelo M. Soares, Springer Science+Business Media B.V., 2024, Vol. 14716, p. 390-400Conference paper, Published paper (Refereed)
Abstract [en]

When bus manufacturing companies move forward in their serviti- zation journey for providing service solutions for tourism industry, there is an increasing need to exploit the prototype way to support the realization of design solutions in the early stages of the Product Service System (PSS) design. Digital twin, a new emerging and fast growing technology which connects the physical and virtual world, has attracted much attention worldwide recently. This paper presents a new method for PSS design based on the digital twin approach. The development of product design is briefly introduced first. The framework of digital twin approach is then proposed and analysed. The main work in this research work is how to trade off the ‘realism’ of the design output of the virtual concept. A case is presented to illustrate the application of the proposed DT approach for prod- uct prototyping. Verification activities performed the case in a virtual simulation environment prototype the design concepts in the tourism industry.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2024. Vol. 14716, p. 390-400
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349
Keywords [en]
Digital Twin, Prototyping, Product Service System, Service scenario, Tour bus
National Category
Vehicle Engineering
Research subject
Mechanical Engineering
Identifiers
URN: urn:nbn:se:bth-26644DOI: 10.1007/978-3-031-61362-3_28ISI: 001275716600028Scopus ID: 2-s2.0-85197283978ISBN: 978-3-031-61361-6 (print)OAI: oai:DiVA.org:bth-26644DiVA, id: diva2:1881311
Conference
13th International Conference on Design, User Experience, and Usability, DUXU 2024, Washington, DC, June 29 – July 04, 2024
Part of project
Model Driven Development and Decision Support – MD3S, Knowledge Foundation
Funder
VinnovaKnowledge Foundation, 20180159Available from: 2024-07-03 Created: 2024-07-03 Last updated: 2025-01-15Bibliographically approved
In thesis
1. Future innovation framework for smart product service system design: Exploring an innovative design approach for global manufacturing companies
Open this publication in new window or tab >>Future innovation framework for smart product service system design: Exploring an innovative design approach for global manufacturing companies
2024 (English)Doctoral thesis, comprehensive summary (Other academic) [Artistic work]
Abstract [en]

Today, the rise of digitalization is reshaping how products are designed, produced, and consumed, challenging conventional product development paradigms. In response, manufacturing companies are increasingly adopting service-oriented business models through digital servitization, fueling the emergence of smart Product Service System (sPSS). However, the inherent complexity and need for collaborative innovation in smart PSS design requires manufacturing companies to adopt innovative design approaches that enable value-adding solutions to customers. This research addresses critical gaps in early-stage of smart PSS design, particularly in leveraging Digital Twins (DT) technology to facilitate value co-creation and support design decision-making. Despite growing interest in Digital Twins and virtual simulations, their practical application in smart PSS design remains limited, highlighting the need for new design approaches that foster collaboration and innovation in the early design stages.  To address these challenges and opportunities, this research integrates literature reviews, case studies, and empirical analysis to propose the Future Innovation Framework (FIF) and the Super-System Digital Twins (SSDT) approach for smart PSS development. Through industrial case studies, the research provides practical insights and introduces a Digital Twins approach that supports the successful implementation of smart PSS design in the context of global manufacturing companies. The findings indicate that the proposed Digital Twins approach significantly enhances concept visualization, decision-making and design prototyping in smart PSS design. Future research should focus on refining the Future Innovation Framework (FIF) and Super-System Digital Twins (SSDT) approach, exploring their scalability across various industries, and incorporating advanced AI techniques to maximize their potential.  In summary, this research contributes to the theoretical and practical advancements in smart PSS design by demonstrating how FIF and SSDT can foster more effective and innovative approach in global manufacturing companies. The proposed approach provides a robust foundation for future research and industrial applications, promoting the development of sustainable and competitive smart PSS solutions.  

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2024. p. 400
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 2024:16
Keywords
Smart Product Service System, smart PSS design, Future Innovation Framework, Digital Twins, Automotive manufacturing company
National Category
Mechanical Engineering
Research subject
Mechanical Engineering
Identifiers
urn:nbn:se:bth-27038 (URN)978-91-7295-490-8 (ISBN)
Public defence
2024-12-18, J1630, Karlskrona, 09:00 (English)
Opponent
Supervisors
Available from: 2024-10-31 Created: 2024-10-30 Last updated: 2025-01-17Bibliographically approved

Open Access in DiVA

The full text will be freely available from 2025-08-04 11:52
Available from 2025-08-04 11:52

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Zhang, YanLarsson, Tobias

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