Title :
Virtual factory revisited for manufacturing data analytics
Author :
Jain, Sonal ; Guodong Shao
Author_Institution :
George Washington Univ., Washington, DC, USA
Abstract :
Development of an effective data analytics application for manufacturing requires testing with large sets of data. It is usually difficult for application developers to find access to real manufacturing data streams for testing new data analytics applications. Virtual factories can be developed to generate the data for selected measures in formats matching those of real factories. The vision of a virtual factory has been around for more than a couple decades. Advances in technologies for computation, communication, and integration and in associated standards have made the vision of a virtual factory within reach now. This paper discusses requirements for a virtual factory to meet the needs of manufacturing data analytics applications. A framework for the virtual factory is proposed that leverages current technology and standards to help identify the developments needed for the realization of virtual factories.
Keywords :
data analysis; virtual manufacturing; manufacturing data analytics; manufacturing data streams; virtual factory revisited; Analytical models; Data analysis; Data models; Manufacturing; Production facilities; Solid modeling; Virtual manufacturing;
Conference_Titel :
Simulation Conference (WSC), 2014 Winter
Conference_Location :
Savanah, GA
Print_ISBN :
978-1-4799-7484-9
DOI :
10.1109/WSC.2014.7019949