REINFORCEMENT LEARNING-BASED OPTIMIZATION OF MANUFACTURING LINES

Technologies for reinforcement learning-based optimization of manufacturing lines are disclosed. A reinforcement learning-based selector is trained utilizing reinforcement learning to select a reinforcement learning-based controller for controlling the operation of machines on a manufacturing line....

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser:	NEEMA, Kartavya, JAFARI, Amir Hossein, CHUNG, Brice Hoani Valentin
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING
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Beschreibung
Zusammenfassung:	Technologies for reinforcement learning-based optimization of manufacturing lines are disclosed. A reinforcement learning-based selector is trained utilizing reinforcement learning to select a reinforcement learning-based controller for controlling the operation of machines on a manufacturing line. The selection can be made based upon inputs from the machines on the manufacturing line indicating whether machines on the line are jammed, whether the manufacturing line is operating at a steady state, or other conditions. The selected reinforcement learning-based controller can generate outputs to adjust parameters of the machines on the manufacturing line, such as operating speed, in order to recover from the jamming of one or more machines, to transition to a steady state of operation, or to operate the manufacturing line in a steady state of operation. The selector and the reinforcement learning-based controllers can be trained using reinforcement learning on a simulation of the manufacturing line.