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Advancing the Development Process of Digital Twins for Production Systems
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0002-2632-1553
2024 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

 

Manufacturing companies are increasingly making substantial investments towards digital twins to enable the continuous optimization of their production processes. To maximize the value of these investments, a structured development process can facilitate faster development, enhance resource planning, and reduce overall costs while simultaneously increasing the probability of successful digital twin developments for production systems. 

Existing literature principally addresses specific steps and challenges within the development process, leaving a need for deeper holistic exploration into how digital twins can be developed in industrial manufacturing settings. This gap represents a significant challenge for manufacturing companies, as the incorrect execution of this process could result in a considerable loss of valuable time and resources.

The purpose of this thesis is to explore the development process of digital twins for production systems. This thesis studies the development process of digital twins within a global manufacturing by adopting real-time longitudinal case study methodology. By focusing on the development process aspects, this licentiate thesis seeks to generate new insights that will be useful to those responsible for or involved in the digital twin development process. 

This thesis provides three main contributions. Firstly, it identifies key requirements when developing digital twins for production systems, highlighting the need to focus on not only technical requirements, but also requirements related to people and processes. Secondly, based on physical, virtual, and process complexity, it identifies the sources of complexity when developing digital twins for production systems. Thirdly, it provides insights into the development activities within digital twin development processes , offering significant guidelines for researchers and practitioners.

This thesis presents a framework that offers a practical contribution to support practitioners in the process of developing digital twins for production systems. It outlines a structured approach to assist practitioners in mitigating the complexities of digital twin development process. The approach outlines key stages and considerations to facilitate the holistic perspective of the process, providing a practical tool for manufacturing companies to enhance their efforts and increase the potential for success in digital twin developments for production systems. 

Place, publisher, year, edition, pages
Eskilstuna: Mälardalens universitet, 2024.
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 368
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Systems
Identifiers
URN: urn:nbn:se:mdh:diva-68746ISBN: 978-91-7485-685-9 (print)OAI: oai:DiVA.org:mdh-68746DiVA, id: diva2:1907519
Presentation
2024-12-04, C3-003, Mälardalens universitet, Eskilstuna, 09:15 (English)
Opponent
Supervisors
Available from: 2024-10-23 Created: 2024-10-22 Last updated: 2024-11-13Bibliographically approved
List of papers
1. Exploring the Development Process of Digital Twins for Manufacturing Firms: A Longitudinal Case
Open this publication in new window or tab >>Exploring the Development Process of Digital Twins for Manufacturing Firms: A Longitudinal Case
(English)Manuscript (preprint) (Other academic)
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-68743 (URN)
Available from: 2024-10-22 Created: 2024-10-22 Last updated: 2024-10-31Bibliographically approved
2. Sources of Complexity in the Development of Digital Twins in Manufacturing
Open this publication in new window or tab >>Sources of Complexity in the Development of Digital Twins in Manufacturing
2024 (English)In: Sustainable Production Through Advanced Manufacturing, Intelligent Automation And Work Integrated Learning, Sps 2024, IOS PRESSNIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS , 2024, p. 299-310Conference paper, Published paper (Refereed)
Abstract [en]

Digital twins have emerged as a critical technology to enable smart production. Digital twins can enhance the current production system by optimizing the current setup and facilitating decision-making based on facts rather than gut feeling. Despite the numerous benefits explored, digital twins have faced many challenges in developing and implementing production systems. Their complexity is causing a lack of digital twin implementations in the production system. This complexity can be traced back to physical and virtual entities and the digital twin development process. By conducting a case study in a global manufacturing company, this publication explores the sources of complexity when developing digital twins. The findings are organized around the digital twin development steps and their corresponding complexity. The number of different types of entities being modeled, the choice of the modeling approach, modeling low-frequency events, emergent phenomena, and the unpredictability and variability of the manufacturing process are all examples of structural and dynamic complexity that have been found to impede success in digital twin applications. This research has implications for managers who are involved in the development of digital twins in their organizations. It can help with methodological guidance when dealing with an undefined and complicated process of digital twin development.

Place, publisher, year, edition, pages
IOS PRESSNIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS, 2024
Keywords
Complexity, Digital Twin Modeling, Simulation, Smart Production, Virtual Models, 'current, Critical technologies, Current production, Decisions makings, Production system, Decision making
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:mdh:diva-66583 (URN)10.3233/ATDE240174 (DOI)2-s2.0-85191348483 (Scopus ID)9781643685106 (ISBN)
Conference
11th Swedish Production Symposium, SPS2024, Trollhattan, 23 April 2024 through 26 April 2024
Available from: 2024-05-08 Created: 2024-05-08 Last updated: 2024-10-23Bibliographically approved
3. Model Simplification: Addressing Digital Twin Challenges and Requirements in Manufacturing
Open this publication in new window or tab >>Model Simplification: Addressing Digital Twin Challenges and Requirements in Manufacturing
2023 (English)In: Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures / [ed] Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D, 2023, p. 287-301Conference paper, Published paper (Refereed)
Abstract [en]

Leveraging the potential of digital twins is of utmost importance to support smart production. Digital twin research has principally focused on defining digital twin concepts and applications and proposing various frameworks for their implementation. Less is known about using simplified models to overcome many challenges related to digital twin models. Based on a longitudinal case study at a multinational manufacturing company engaged in digital twins in manufacturing efforts, this paper identifies the main challenges encountered related to people, processes, and technology, as well as requirements placed on a digital twin. This study also presents the opportunities of applying simplified models for digital twins to overcome the identified challenges and fulfill the defined requirements. The present study provides theoretical and practical implications of the development of digital twins in manufacturing, focusing attention on the challenges and requirements that affect the outcome of the manufacturing company to drive digital twin efforts.

National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:mdh:diva-64538 (URN)10.1007/978-3-031-43666-6_20 (DOI)2-s2.0-85174445280 (Scopus ID)978-3-031-43665-9 (ISBN)978-3-031-43666-6 (ISBN)
Conference
IFIP International Conference on Advances in Production Management Systems, APMS 2023
Available from: 2023-10-17 Created: 2023-10-17 Last updated: 2024-10-22Bibliographically approved

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Sanchez de Ocaña, Adrian

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