Patent ID: 11860592
Assignee: FORD GLOBAL TECHNOLOGIES, LLC
Field: Control (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. A method for training a reinforcement learning system, the method comprising:
obtaining state information from one or more sensors of a digital twin, wherein the state information includes a number of a plurality of pallets at a first routing control location of the digital twin during a manufacturing simulation, a type of the plurality of pallets at the first routing control location during the manufacturing simulation, or a combination thereof;
determining an action at the first routing control location based on the state information, wherein the action includes one of a pallet merging operation and a pallet splitting operation;
determining a consequence state based on the action, wherein the consequence state includes a consequent number of the plurality of pallets at a consequent routing control location of the digital twin, a type of the plurality of pallets at the consequent routing control location, or a combination thereof;
calculating a transient production value based on the consequence state and a transient objective function;
calculating a steady state production value based on the consequence state and a steady state objective function; and
selectively adjusting one or more reinforcement parameters of the reinforcement learning system based on the transient production value and the steady state production value.