TOWARDS SMART MANUFACTURING WITH VIRTUAL FACTORY AND DATA ANALYTICS
| Autor: | Jain, Sanjay, Lechevalier, David, Narayanan, Anantha |
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| Přispěvatelé: | George Washington University School of Business, Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), University of Maryland [College Park], University of Maryland System, National Institute of Standards and Technology's Guest Researcher Program 70NANB14H250, Chan, V, DAmbrogio, A, Zacharewicz, G, Mustafee, N, université de Bourgogne, LE2I |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | 2017 WINTER SIMULATION CONFERENCE (WSC) Winter Simulation Conference (WSC) Winter Simulation Conference (WSC), Dec 2017, Las Vegas, NV, United States. pp.3018-3029 |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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