https://doi.org/10.1109/MIS.2021.3062437

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Document Type

Article

Subject Area(s)

Artificial Intelligence, Industry 4.0, Smart Manufacturing

Abstract

Smart manufacturing or Industry 4.0, a trend initiated a decade ago, aims to revolutionize traditional manufacturing using technology-driven approaches. Modern digital technologies such as the Industrial Internet of Things (IIoT), Big Data Analytics, Augmented/Virtual Reality, and Artificial Intelligence (AI) are the key enablers of new smart manufacturing approaches. The digital twin is an emerging concept whereby a digital replica can be built of any physical object. Digital twins are becoming mainstream; many organizations have started to rely on digital twins to monitor, analyze, and simulate physical assets and processes. The current use of digital twins for smart manufacturing is largely limited to (i) status monitoring, (ii) simulation, and (iii) visualization. For status monitoring, digital replicas of physical assets (e.g., machines) are created, machines are continuously monitored using IIoTs, and the latest status of a machine can be assessed by querying its digital twin. For simulation, digital twins of machines, processes, and products are created to mimic real settings. Simulation allows the design, development, and testing of new products and processes using their digital twins before applying them to actual physical assets, this is presented in. For visualization, digital twins can include real-time dashboards and alert systems to monitor and debug an operational environment. However, in contemporary cases, digital twins are simply considered to be an exact replica of the physical assets, without any value-added services built on top of them which could convert physical assets into autonomous intelligent agents. A major advantage of this enhanced design of digital twins is that they can offer much more than just an exact replica to support value-added services on top of digital twins, which are not possible on the physical assets.

Digital Object Identifier (DOI)

https://doi.org/10.1109/MIS.2021.3062437

APA Citation

Ali, M. I., Patel, P., Breslin, J. G., Harik, R., & Sheth, A. (2021). Cognitive digital twins for smart manufacturing. IEEE Intelligent Systems. https://doi.org/10.1109/MIS.2021.3062437

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