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Course Outline
Overview of 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 for Demand Forecasting
- Time-series forecasting using machine learning techniques.
- Managing seasonality and trend variables.
- Enhancing forecast precision through historical data analysis.
Inventory Optimization and Replenishment
- AI-based prediction of stock levels.
- Calculations for safety stock and reorder points.
- Integrating AI systems with ERP and WMS platforms.
Route Optimization and Fleet Intelligence
- Shortest path algorithms and delivery routing strategies.
- Dynamic route planning that accounts for traffic conditions.
- AI-supported transport scheduling.
Warehouse Automation and Robotics
- Applying AI to picking, sorting, and storage automation.
- Utilizing computer vision for shelf monitoring.
- Coordination with AGVs and robotic arms.
Real-Time Analytics and Dashboarding
- Creating live dashboards using Tableau and Python.
- Tracking KPIs via real-time data streams.
- Setting up alerts and handling exceptions.
Case Study and Capstone Project
- Analyzing complex multi-node supply chain scenarios.
- Applying forecasting and routing models in practice.
- Presenting a data-driven plan for logistics optimization.
Summary and Next Steps
Requirements
- Familiarity with supply chain or logistics operations.
- Experience in data analysis or business intelligence tools.
- Basic proficiency in programming or scripting.
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