Data driven production modeling and simulation of complex automobile general assembly plant

  • Authors:

  • Junfeng Wang;Qing Chang;Guoxian Xiao;Nan Wang;Shiqi Li

  • Affiliations:

  • Department of Industrial and Manufacturing System Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China;Department of Mechanical Engineering, New York Institute of Technology, Old Westbury, NY 11568, USA;Manufacturing Systems Research Lab, General Motors Research and Development Center, Warren, MI 48090, USA;Department of Industrial and Manufacturing System Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China;Department of Industrial and Manufacturing System Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

  • Venue:
  • Computers in Industry
  • Year:
  • 2011

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Abstract

Flexible manufacturing and customization has long been a topic in modern manufacturing society. However, challenges still remain on the responsiveness of production system to the fluctuation of market demand. In this paper, we developed a data driven simulation methodology to automatically model a production system and rapidly modify the model corresponding to dynamic requirements and real time information. This methodology provides a ''rapid prototyping'' capability for production system modeling and enables a quick analyzing and remodeling capability to respond to the fluctuation of demands. The approach is developed and applied to an automotive general assembly plant with an online material handling system. A complete information model based on IDEF1X is constructed for this domain specific modeling and simulation. The main simulation modules for assembly line and material handling system of the plant floor are analyzed and a simulator is implemented in ARENA by SIMAN/VBA program. The case study of an automotive assembly plant shows that the data driven approach enables the modeling and simulation of the complex assembly plant in a ''real-time'' fashion and therefore effectively improve the responsiveness and flexibility of the production line.