Method for self-learning manufacturing scheduling for a flexible manufacturing system by using a state matrix and device

Abstract

The method for self-learning manufacturing scheduling for a flexible manufacturing system (FMS) with processing entities that are interconnected through handling entities is disclosed. The manufacturing scheduling is learned by a reinforcement learning system on a model of the flexible manufacturing system. The model represents at least the behavior and the decision making of the flexible manufacturing system, and the model is transformed in a state matrix to simulate the state of the flexible manufacturing system. A self-learning system for online scheduling and resource allocation is also provided. The system is trained in a simulation and learns the best decision from a defined set of actions for many every situation within an FMS. A decision may be made in near real-time during a production process and the system finds the optimal way through the FMS for every product using different optimization goals.

Dependencies are inferred from the claim text.