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Communication dans un congrès

TOWARDS SMART MANUFACTURING WITH VIRTUAL FACTORY AND DATA ANALYTICS

Abstract : Virtual factory models can help improve manufacturing decision making when augmented with data analytics applications. Virtual factory models provide the capability of simulating real factories and generating realistic data streams at the desired level of resolution. Deeper insights can be gained and underlying relationships quantified by channeling the simulation output data to an external analytics tool. This paper describes integration of a virtual factory prototype with a neural network analytics application. The combined capability is used to create a neural network capable of predicting the expected cycle times for a small job shop. The capability can adapt by retraining the neural network whenever the production circumstances change significantly. The trained neural network can be used for functions such as order promising and can support factory management. The analytical and adaptive combination represented by the virtual factory integrated with the neural network thus supports the move towards smart manufacturing.
Keywords : BIG DATA
Type de document :
Communication dans un congrès
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01857956
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : vendredi 17 août 2018 - 16:58:56
Dernière modification le : vendredi 17 juillet 2020 - 14:59:07

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  • HAL Id : hal-01857956, version 1

Citation

Sanjay Jain, David Lechevalier, Anantha Narayanan. TOWARDS SMART MANUFACTURING WITH VIRTUAL FACTORY AND DATA ANALYTICS . Winter Simulation Conference (WSC), Dec 2017, Las Vegas, NV, United States. pp.3018-3029. ⟨hal-01857956⟩

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