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Communication Dans Un Congrès Année : 2022

Toward a sawmill digital shadow based on coupled simulation and supervised learning models

Résumé

Digital Twins (DT) have been introduced as promising decision support tools in many different settings and to serve a variety of purposes. Many challenges are raised by their development, including an efficient usage of their computational resources to balance performance on precision, computational cost and speed. This study is, in particular, concerned with Digital Shadows (DS), a concept derived from DT, applied to sawmills sawing production units. A method to combine a computationally intensive sawmill simulation model with a machine learning model is proposed to predict set of lumbers sawed from logs. Numeric experiments are exposed, and the proposed method demonstrate improvements from 11% to 18% of the monitored couple regret from its baseline.
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Dates et versions

hal-03835261 , version 1 (31-10-2022)

Identifiants

  • HAL Id : hal-03835261 , version 1

Citer

Sylvain Chabanet, Hind Bril El Haouzi, Philippe Thomas. Toward a sawmill digital shadow based on coupled simulation and supervised learning models. 12th International Workshop on Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future, SOHOMA’22, Sep 2022, Bucharest, Romania. ⟨hal-03835261⟩
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