AI for Supply Chain and Manufacturing Logistics

• An understanding of supply chain or logistics operations
• Experience with data analysis or business intelligence tools
• Basic familiarity with programming or scripting

Audience

• Supply chain analysts
• Logistics managers
• Industrial planners

AI in Supply Chain and Manufacturing Logistics is the application of predictive analytics, machine learning, and automation to optimize inventory, routing, and demand forecasting.

This instructor-led, live training (online or onsite) is aimed at intermediate-level supply chain professionals who wish to apply AI-driven tools to enhance logistics performance, forecast demand accurately, and automate warehouse and transport operations.

By the end of this training, participants will be able to:

• Understand how AI is applied across logistics and supply chain activities.
• Use machine learning models for demand forecasting and inventory control.
• Analyze routes and optimize transport using AI-based techniques.
• Automate decision-making in warehouses and fulfillment processes.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Overview of AI in Supply Chain and Logistics

• Emerging trends in smart logistics
• AI vs. traditional analytics in supply chain management
• Key technologies and platforms

AI for Demand Forecasting

• Time-series forecasting with machine learning
• Handling seasonality and trend components
• Improving forecast accuracy with historical data

Inventory Optimization and Replenishment

• AI-driven stock level prediction
• Safety stock and reorder point calculations
• Integrating AI with ERP and WMS

Route Optimization and Fleet Intelligence

• Shortest path algorithms and delivery routing
• Traffic-aware dynamic route planning
• AI-enabled transport scheduling

Warehouse Automation and Robotics

• AI in picking, sorting, and storage automation
• Computer vision for shelf monitoring
• Coordinating with AGVs and robotic arms

Real-Time Analytics and Dashboarding

• Live dashboards with Tableau and Python
• Monitoring KPIs with real-time data streams
• Generating alerts and exception handling

Case Study and Capstone Project

• Analyzing a multi-node supply chain scenario
• Applying forecasting and routing models
• Presenting a data-driven logistics optimization plan

Summary and Next Steps