An AI-Enabled Simulation: Applying Neural Network in a Flexible Flow Shop Problem

Simulation modeling is integral to the successful implementation of Digital Twin. As Digital Twin models become increasingly sophisticated, it is crucial to enhance the capabilities of simulation modeling by incorporating AI-enabled techniques. By leveraging the power of AI, such as deep learning and artificial neural networks, simulation modeling can be enhanced to provide more accurate and efficient predictions. This paper applies a neural network model within a simulation environment to facilitate decision-making in an assembly line setting. After training, the intelligent data-driven neural network model selects the server in real-time for each job. The Simio Neural Network tool is utilized to collect data, train the neural network model, and conduct experiments. According to the experimental results, the trained neural network model outperforms the baseline model solution.