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Condition-based Real-time Production Control for Smart Manufacturing Systems

Published

Author(s)

Yan Lu, Feifan Wang, Feng Ju

Abstract

In this paper, we present condition-based real-time production control for smart manufacturing which is aimed at improving system performance by automatically assessing a production system's condition and dynamically configuring the processing routes for smart products/parts. A machine's degradation condition is defined in discrete states and modeled as a Markov chain. By taking into account machines' degradation and buffers' occupancy, an optimization problem is formulated to maximize the production rate using Markov Decision Processes. The effectiveness of the method has been demonstrated on a three-machine flexible production system. The implementation challenges of condition-based production control are discussed, with the existing and missing enabling standards identified and analyzed.
Proceedings Title
Proc. of IEEE Conference on Automation Science and Engineering 2018
Conference Dates
August 20-24, 2018
Conference Location
Munich, DE
Conference Title
13th IEEE Conference on Automation Science and Engineering 2018

Keywords

smart manufacturing, condition based production, Markov chain processes

Citation

Lu, Y. , Wang, F. and Ju, F. (2018), Condition-based Real-time Production Control for Smart Manufacturing Systems, Proc. of IEEE Conference on Automation Science and Engineering 2018, Munich, DE, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=925590 (Accessed May 26, 2024)

Issues

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Created August 19, 2018, Updated April 19, 2022