Recently, the production environment has been rapidly changing, and accordingly, correct mid term and short term decision-making for production is considered more important. Reliable indicators are required for correct decision-making, and the manufacturing cycle time plays an important role in manufacturing. A method using digital twin technology is being studied to implement accurate prediction, and an approach utilizing process discovery was recently proposed. This paper proposes a digital twin discovery framework using process transition technology. The generated digital twin will unearth its characteristics in the event log. The proposed method was applied to actual manufacturing data, and the experimental results demonstrate that the proposed method is effective at discovering digital twins.
CITATION STYLE
Yang, M., Moon, J., Jeong, J., Sin, S., & Kim, J. (2022). A Novel Embedding Model Based on a Transition System for Building Industry-Collaborative Digital Twin. Applied Sciences (Switzerland), 12(2). https://doi.org/10.3390/app12020553
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