Condition-based Real-time Production Control for Smart Manufacturing Systems
Yan Lu, Feifan Wang, Feng Ju
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.
Proc. of IEEE Conference on Automation Science and Engineering 2018
August 20-24, 2018
13th IEEE Conference on Automation Science and Engineering 2018
, Wang, F.
and Ju, F.
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 December 4, 2023)