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Modeling and Performance Identification for General Production System Using Sensor Data

[+] Author Affiliations
Jing Zou, Qing Chang

Stony Brook University, Stony Brook, NY

Yong Lei

Zhejiang University, Hangzhou, Zhejiang, China

Jorge Arinez, Guoxian Xiao

General Motors R&D, Warren, MI

Paper No. MSEC2016-8506, pp. V002T04A020; 7 pages
doi:10.1115/MSEC2016-8506
From:
  • ASME 2016 11th International Manufacturing Science and Engineering Conference
  • Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing
  • Blacksburg, Virginia, USA, June 27–July 1, 2016
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-4990-3
  • Copyright © 2016 by ASME and General Motors

abstract

The productivity and efficiency of production systems are greatly influenced by their configuration and complex dynamics subject to constant changes caused by technology insertion, engineering modification, as well as disruption events. In this paper, we develop a mathematical model of production systems with general structure (tandem line, parallel, and etc.) to estimate the status of the system (production counts and processing speeds of the stations, buffer levels and production loss) by using sensor data of disruption events. Real-time production system performance such as effective disruption events, opportunity window, and permanent production loss are identified, which is very useful in real-time control to increase overall system efficiency.

Copyright © 2016 by ASME and General Motors

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