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Course Outline
Introduction to AI in Supply Chain and Logistics
- Current trends in smart logistics
- Comparing AI with traditional analytics in supply chain management
- Essential technologies and platforms
AI-Powered Demand Forecasting
- Applying machine learning to time-series forecasting
- Managing seasonality and trend elements
- Enhancing forecast precision using historical data
Inventory Optimization and Replenishment Strategies
- Predicting stock levels using AI
- Calculating safety stock and reorder points
- Integrating AI with ERP and WMS systems
Route Optimization and Fleet Intelligence
- Shortest path algorithms and delivery routing strategies
- Dynamic route planning considering traffic conditions
- AI-enhanced transport scheduling
Warehouse Automation and Robotics Integration
- AI applications in picking, sorting, and storage automation
- Utilizing computer vision for shelf monitoring
- Coordinating with AGVs and robotic arms
Real-Time Analytics and Dashboard Development
- Creating live dashboards with Tableau and Python
- Tracking KPIs via real-time data streams
- Implementing alerts and exception handling mechanisms
Case Study and Capstone Project
- Evaluating a multi-node supply chain scenario
- Deploying forecasting and routing models
- Presenting a data-driven logistics optimization strategy
Conclusion and Future Directions
Requirements
- A foundational understanding of supply chain or logistics operations
- Practical experience with data analysis or business intelligence tools
- Basic knowledge of programming or scripting languages
Target Audience
- Supply chain analysts
- Logistics managers
- Industrial planners
21 Hours
Testimonials (2)
The input fm other industries through the trainer.
Lars Schacht - Scandlines Danmark ApS
Course - Advanced Sales and Operations Planning (S&OP) for Demand Forecasting
I liked the most that the trainer was professional, highly skilled in his domain of activity and very friendly towards us. 10/10
