Matthias Mueller

Supply Chain Management has recently prioritized resiliency over mere efficiency, driven by frequent disruptions. Leveraging advanced AI, we aim to transform planning into a decision-centric and autonomous process by optimizing data use. Our vision is to simplify complexity, reduce anxiety, and enable resilient AI-driven planning and decision-making. This empowers businesses to make timely, high-quality decisions, ensuring ERP data accuracy and seamless alignment across the supply chain, particularly in manufacturing and production control, enhancing performance and adaptability in the face of market changes.

In a world of constant disruption—from geopolitical shifts to raw material shortages — traditional supply chains are no longer sufficient. This session explores the cutting-edge pursuit of “self-healing” supply chains -- intelligent, adaptive networks that detect issues, reroute resources, and restore operations with minimal human intervention.

We’ll examine how manufacturers are leveraging AI, IoT, and predictive analytics to build supply chains that don’t just react—they recover. Learn how these innovations are driving smoother production flows, reducing downtime, and enabling higher manufacturing output even in volatile conditions.

Key Takeaways:

• What defines a “self-healing” supply chain—and why it matters now
• Technologies enabling autonomous detection and correction of disruptions
• How to architect supply networks for agility, visibility, and resilience
• Real-world examples of self-healing systems boosting throughput and reliability