Demo - Decision Maker - Problem - Online Decision

Graphic model

Real-Time Decision Maker for Production Line

Overview

This web-based system utilizes a Stochastic Differential Equation (SDE)-based AI model to simulate real-time decision-making for a production line. The machine's operational parameters are constantly monitored, and decisions are made regarding whether the system is operating optimally or requires attention. The results are displayed in a table, providing continuous updates on key parameters such as temperature, vibration, and speed.

Key Concepts

1. Stochastic Differential Equation (SDE): The state of the machine evolves according to an SDE model, where the state vector consists of parameters like temperature, vibration, and speed.

2. Real-Time Decision-Making: A function classifies the machine's operational state:

   • Optimal: Machine parameters are within safe operational ranges.

   • Warning: Parameters are showing moderate deviations, which could lead to issues.

   • Critical: Parameters fall outside safe operational thresholds, indicating an immediate need for intervention.

3. Visualization: The machine's operational parameters and their statuses are displayed in a table that updates every 2 seconds, allowing real-time monitoring of the production line.

Features

• Real-Time Updates: The simulation updates every 2 seconds, showing the evolving machine parameters.

• Dynamic Classification: Each state is classified into one of three categories: Optimal, Warning, or Critical based on predefined thresholds.

• Interactive Table: The table displays key parameters (temperature, vibration, speed) and their status, keeping the most recent 10 updates visible.

Applications

✔ Manufacturing: Helps in predictive maintenance, identifying potential issues before they affect production.
✔ Process Control: Used to optimize machine performance and avoid operational inefficiencies.
✔ Industrial IoT: Continuously monitors and evaluates machines in a smart factory setting.