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Course Outline
Overview of AI in Supply Chain and Logistics
- Emerging trends in smart logistics
- AI compared to traditional analytics in supply chain management
- Core technologies and platforms
AI for Demand Forecasting
- Time-series forecasting using machine learning
- Managing seasonality and trend factors
- Enhancing forecast precision through historical data analysis
Inventory Optimization and Replenishment
- AI-driven prediction of stock levels
- 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 sensitive to traffic conditions
- AI-enabled scheduling for transport
Warehouse Automation and Robotics
- AI applications in picking, sorting, and storage automation
- Utilizing computer vision for shelf monitoring
- Coordinating with AGVs and robotic arms
Real-Time Analytics and Dashboarding
- Creating live dashboards using Tableau and Python
- Monitoring KPIs via real-time data streams
- Setting up alerts and handling exceptions
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
Requirements
- A foundational understanding of supply chain or logistics operations
- Prior experience with data analysis or business intelligence platforms
- 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