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Sanjay Jain, Guodong Shao, Seungjun Shin


Manufacturing organizations are able to accumulate large amounts of plant floor production and environmental data due to advances in data collection, communications technology, and use of standards. Data analytics can help understand and gain insights from the collected big data and in turn help advance towards the vision of smart manufacturing. Modeling and simulation (M&S) have been used by manufacturers to analyze their operations and support decision making. M&S can be used to develop a virtual factory representation of a real factory. A framework for the virtual factory is presented that leverages current technology and standards to help identify the developments needed for the realization of virtual factories. The paper proposes use of a virtual factory representation in multiple ways to support data analytics in manufacturing environment. The virtual factory can be used as a data analytics application itself and it can also be used to support other such applications. An example case is presented that demonstrates the use of a virtual representation of a turning machine to generate the data required to support manufacturing data analytics applications.
International Journal of Production Economics


Big data, modeling, simulation, virtual machine, data generator.


Jain, S. , Shao, G. and Shin, S. (2017), MANUFACTURING DATA ANALYTICS USING A VIRTUAL FACTORY REPRESENTATION, International Journal of Production Economics (Accessed April 23, 2024)
Created July 6, 2017