Date: 2023-06-04 Program: Degree of Master of Science in Engineering - Product and Process Development Author: Beraz Omar & Randy Shamorad Title: Data value chain for a Digital Twin in a manufacturing company Supervisors: Nathalie Agerskans & Jessica Bruch Keywords: Industry 4.0, data value chain, Internet of Things (IoT), Digital Twin (DT), Big data (BD), Artificial Intelligence (AI), Cloud computing, Fog computing, enablers & challenges. Background: Industry 4.0 is a shared term for digital technologies that through interaction and integration with each other can create opportunities for companies. An example of a digital technology is Digital Twin. Digital Twin is a virtual copy or model of a physical product, system or process that is directly connected through an Internet connection for the purpose of transferring real-time data between the virtual world and reality. There are challenges in providing the Digital Twin with real-time data through a data value stream. Purpose: The purpose of this study is to create a data value flow using digital technologies from industry 4.0 that will support the creation of a Digital Twin within internal logistics. Research questions: • What challenges exist when creating data value flows for a Digital Twin in internal logistics? • What are the critical factors when creating a data value flow for a Digital Twin in internal logistics? • How to create a data value flow for a Digital Twin within internal logistics? Method: This study is based on a qualitative research strategy and a case study where the empirical findings have been collected through participant observation, semi-structured interviews and notes from the case company. The theoretical chapter is based on a literature study. The collected data has undergone a four-part data analysis process to fulfill what the study demands. Conclusion: The conclusion of the study presents challenges and critical factors as well as the approach of how to create a data value chain for a Digital Twin in internal logistics. The challenges are many, as the creation of a data value chain can be an extensive change. Identification of critical factors will be required to be able to make the right efforts that create the complete data value chain for Digital Twin. Comparison and analysis between different digital technologies is required to be able to select the optimal technologies for a specific investment. These digital technologies shall support the data value flow with the following steps, generation, collection, movement, storage and analysis of data. The study has concluded that the integration of sensors, laser marking, Internet of Things, Big data, Cloud computing is required to create an optimal data value flow for a Digital Twin for the specific case company.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mdh-62837 |
| Date | January 2023 |
| Creators | Shamorad, Randy, Omar, Beraz |
| Publisher | Mälardalens universitet, Akademin för innovation, design och teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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