Dark Factory: Orchestrating Autonomous Software & Robots

Establish the architectural principles of 'lights-out' operations where AI agents replace human intervention. You will learn to map backend services to physical workflows u…

Course outline

1. Foundations of Dark Factory Orchestration

   Establish the architectural principles of 'lights-out' operations where AI agents replace human intervention. You will learn to map backend services to physical workflows using autonomous logic.

2. The Dark Factory Paradigm

   Define the transition from automated to autonomous systems in software and hardware. You will identify the key differences between traditional CI/CD and self-healing industrial loops.

3. MQTT & Sparkplug B Architecture

   Master the state-aware messaging protocol essential for industrial IoT. You will design a unified namespace for real-time device communication.

4. AI Agent Orchestration & Logic

   Develop the brain of the factory using AI agents that can reason and execute tasks. You will build orchestration layers that manage complex physical dependencies.

5. Agentic Workflow Design

   Learn to break down industrial tasks into sub-goals for AI agents. You will implement planning algorithms that handle non-deterministic environments.

6. ML-Driven Recovery Logic

   Implement reinforcement learning and heuristic models for error recovery. You will create systems that detect anomalies and autonomously reroute production tasks.

7. Physical-Digital Integration

   Bridge the gap between backend backend code and physical actuators. You will simulate and then deploy orchestration logic to hardware-in-the-loop environments.

8. Digital Twins for Orchestration

   Build high-fidelity digital shadows of your factory floor. You will use these twins to validate AI decisions before they reach the physical layer.

9. Edge-to-Cloud Data Loops

   Configure low-latency data pipelines between factory edge devices and cloud-based AI controllers. You will optimize for sub-millisecond response times in critical paths.