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Leveraging Digital Twins for Value-Driven Design in Smart Product-Service Systems: The Super-System Digital Twin Framework and SEV Case Study
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0003-3711-264X
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0002-5076-3300
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0001-5114-4811
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0003-2211-2436
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2025 (English)In: Design Science, E-ISSN 2053-4701, Vol. 11, article id e24Article in journal (Refereed) Published
Abstract [en]

Recent academic contributions explore the integration of Digital Twins (DTs) within smart Product-Service System (sPSS). This integration aims to innovate business propositions, hardware and services. However, gaps persist in developing DT environments to support early-stage collaborative innovation for sPSS, and limited studies explore how real-time synchronized digital replicas enhance value co-creation in this area. This paper addresses this gap by presenting a framework and practical example of integrating value-driven decision support into early sPSS conceptual design. A case study on the development of the Smart Electric Vehicle (SEV) conducted with a global automotive Original Equipment Manufacturer (OEM) demonstrates the framework’s efficacy. Through qualitative data analyses based on experimental validation in a case company, the DT proves effective in aiding decision makers in selecting value-adding configurations within specific scenarios. Furthermore, the DT serves as a visual decision-making tool, fostering collaboration across diverse teams within the automotive company. This collaboration facilitates value creation across practitioners with varied backgrounds, emphasizing the DT’s role in enhancing early-stage innovation and co-creation processes in the sPSS domain.

Place, publisher, year, edition, pages
Cambridge University Press, 2025. Vol. 11, article id e24
Keywords [en]
Digital Twin, Smart Product-Service System, Value-Driven Design, Simulation, Automotive Industry
National Category
Other Mechanical Engineering
Research subject
Mechanical Engineering
Identifiers
URN: urn:nbn:se:bth-27377DOI: 10.1017/dsj.2025.10011ISI: 001522417200001Scopus ID: 2-s2.0-105010171529OAI: oai:DiVA.org:bth-27377DiVA, id: diva2:1927902
Part of project
Model Driven Development and Decision Support – MD3S, Knowledge Foundation
Funder
VinnovaKnowledge Foundation, 20120278Available from: 2025-01-15 Created: 2025-01-15 Last updated: 2025-09-30Bibliographically 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: 2025-09-30Bibliographically approved

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Zhang, YanBertoni, MarcoBertoni, AlessandroLarsson, AndreasLarsson, Tobias

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