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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.
- Overview of key technologies and platforms.
AI for Demand Forecasting
- Time-series forecasting techniques using machine learning.
- Managing seasonality and trend components.
- Enhancing forecast accuracy through historical data analysis.
Inventory Optimization and Replenishment
- 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 with traffic awareness.
- AI-enabled transport scheduling.
Warehouse Automation and Robotics
- Applying AI to picking, sorting, and storage automation.
- Using computer vision for shelf monitoring.
- Coordinating AGVs and robotic arms.
Real-Time Analytics and Dashboarding
- Creating live dashboards using Tableau and Python.
- Monitoring KPIs via real-time data streams.
- Generating alerts and handling exceptions.
Case Study and Capstone Project
- Analyzing a multi-node supply chain scenario.
- Implementing forecasting and routing models.
- Presenting a data-driven logistics optimization plan.
Summary and Next Steps
Requirements
- A solid understanding of supply chain or logistics operations.
- Proficiency in 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
