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Real-time vision-based multiple object tracking of a production process: Industrial digital twin case study
| Content Provider | SAGE Publishing |
|---|---|
| Author | Ward, Robert Soulatiantork, Payam Finneran, Shaun Hughes, Ruby Tiwari, Ashutosh |
| Copyright Year | 2021 |
| Abstract | The adoption of Industry 4.0 technologies within the manufacturing and process industries is widely accepted to have benefits for production cycles, increase system flexibility and give production managers more options on the production line through reconfigurable systems. A key enabler in Industry 4.0 technology is the rise in Cyber-Physical Systems (CPS) and Digital Twins (DTs). Both technologies connect the physical to the cyber world in order to generate smart manufacturing capabilities. State of the art research accurately describes the frameworks, challenges and advantages surrounding these technologies but fails to deliver on testbeds and case studies that can be used for development and validation. This research demonstrates a novel proof of concept Industry 4.0 production system which lays the foundations for future research in DT technologies, process optimisation and manufacturing data analytics. Using a connected system of commercial off-the-shelf cameras to retrofit a standard programmable logic controlled production process, a digital simulation is updated in real time to create the DT. The system can identify and accurately track the product through the production cycle whilst updating the DT in real-time. The implemented system is a lightweight, low cost, customable and scalable design solution which provides a testbed for practical Industry 4.0 research both for academic and industrial research purposes. |
| Related Links | https://journals.sagepub.com/doi/pdf/10.1177/09544054211002464?download=true |
| Starting Page | 1861 |
| Ending Page | 1872 |
| Page Count | 12 |
| ISSN | 09544054 |
| Issue Number | 11 |
| Volume Number | 235 |
| Journal | Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (PIB) |
| e-ISSN | 20412975 |
| DOI | 10.1177/09544054211002464 |
| Language | English |
| Publisher | Sage Publications UK |
| Publisher Date | 2021-03-12 |
| Publisher Place | London |
| Access Restriction | Open |
| Rights Holder | © IMechE 2021 |
| Subject Keyword | cyber-physical production systems real time vision tracking smart manufacturing industry 4.0 multiple object tracking Digital twin |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Mechanical Engineering |
