BACKGROUND - The development of Industry 4.0 increases the opportunities to both automate and digitize processes in the manufacturing industry. The steel industry has been around for many years, which means firmly anchored operations and both manual- and automated processes. To make better decisions, identify bottlenecks, and test new functions without having to stop the production, a digital model of the process can be helpful. Furthermore, with the rapid development of technology, digital models can be further developed into digital twins. A digital twin should be able to handle the communication between the physical- and digital world automatically and analyze data to make decisions in the process. RESEARCH QUESTIONS What are the challenges of developing a digital model representing a production line within a global steel manufacturing company? What opportunities could a digital model of a production line entail, and how could Industry 4.0 technologies create opportunities to further develop the digital model into a digital twin? METHODS - In this project, both a literature- and case study have been carried out. During the literature study, techniques that can be used to develop the digital model further have been investigated. During the case study, a digital model of a Quench Line was developed to gather practical experience of what it can mean to create a digital model of a manufacturing process within a steel manufacturing company. The model has been developed in MATLAB/Simulink. RESULTS - The most significant challenges when developing digital flow simulation models identified in this project were data management/access, handling variations, verifying the model, andlack of knowledge linked to digital models in general. The opportunities identified and confirmed in this project were that the model could be used to carry out new logistics planning, bottleneck analyses, and test new machine implementations. To further develop the digital model into a digital twin, Industry 4.0 technologies will be crucial. The technologies that will be useful are the Internet of Things, Artificial Intelligence, Machine Learning, Cloud Computing, and Big Data.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mdh-59348 |
| Date | January 2022 |
| Creators | Lindblad, Amanda |
| Publisher | Mälardalens universitet, Akademin för innovation, design och teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| 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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