AI-Driven Supply Chain Optimization: From Factory Floor to Global Network

Supply chain optimization in modern manufacturing demands more than dashboards—it requires closed-loop execution. This executive panel explores how Industrial AI operationalizes continuous improvement frameworks like PDCA (Plan-Do-Check-Act) and DDI (Data-Driven Intelligence) to transform traditional planning models such as MPS (Master Production Scheduling) into dynamic, synchronized, and performance-optimized systems.

Designed for Heads of Manufacturing, this session dives into how AI connects planning, scheduling, and shop-floor execution through real-time synchronization (Sync) and POSS (Plan-Optimize-Simulate-Sustain) methodologies. Panelists will share how leading manufacturers are moving from static forecasts to adaptive, AI-driven supply networks that continuously learn and improve.

Key Discussion Points:

• Applying PDCA in an AI-enabled supply chain environment (continuous feedback loops)

• Turning raw operational data into DDI for proactive decision-making

• Reinventing MPS with machine learning and constraint-based optimization

• Real-time Sync between ERP, MES, and plant floor systems

• Leveraging POSS to simulate risk, optimize throughput, and sustain gains

• Aligning supply chain KPIs with enterprise AI strategy

• Change management: embedding AI into manufacturing culture

This session will provide a practical blueprint for building a self-correcting, AI-powered supply chain that drives agility, resilience, and measurable ROI.