Self-learning manufacturing scheduling for a flexible manufacturing system and device
AssigneeSiemens Aktiengesellschaft
InventorSchirin Bär
Life of this patent
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Abstract
A method that is used for self-learning manufacturing scheduling for a flexible manufacturing system that is used to produce at least a product is provided. The manufacturing system consists of processing entities that are interconnected through handling entities. The manufacturing scheduling will be learned by a reinforcement learning system on a model of the flexible manufacturing system. The model represents at least a behavior and a decision making of the flexible manufacturing system. The model is realized as a petri net. An order of the processing entities and the handling entities is interchangeable, and therefore, the whole arrangement is very flexible.
Claims16
A method for self-learning manufacturing scheduling for a flexible manufacturing system that is used to produce at least a product, wherein the flexible manufacturing system includes processing entities that are interconnected through handling entities, the method comprising:
- learning, by a reinforcement learning system, the manufacturing scheduling based on a model of the flexible manufacturing system,
- wherein the model represents at least a behavior and a decision making of the flexible manufacturing system, and
- wherein the model is realized as a petri net.
A reinforcement learning system for self-learning manufacturing scheduling for a flexible manufacturing system that is used to produce at least a product, wherein the flexible manufacturing system includes processing entities that are interconnected through handling entities, the reinforcement learning system comprising:
- a processor configured to:
- learn the manufacturing scheduling based on an input to a learning process, the input including a model of the flexible manufacturing system,
- wherein the model represents at least a behavior and a decision making of the flexible manufacturing system, and
- wherein the model is realized as a petri net.
Dependencies are inferred from the claim text.