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Duration 21 hours
Course Outline
Overview of AI in Supply Chain and Logistics
- Emerging trends in smart logistics.
- Comparing AI with traditional analytics in supply chain management.
- Key technologies and platforms.
AI for Demand Forecasting
- Time-series forecasting using machine learning.
- Managing seasonality and trend components.
- Enhancing forecast accuracy using historical data.
Inventory Optimisation and Replenishment
- AI-driven stock level prediction.
- Calculating safety stock and reorder points.
- Integrating AI with ERP and WMS.
Route Optimisation 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 using Tableau and Python.
- Monitoring KPIs via real-time data streams.
- Generating alerts and handling exceptions.
Case Study and Capstone Project
- Analysing a multi-node supply chain scenario.
- Applying forecasting and routing models.
- Presenting a data-driven logistics optimisation plan.
Summary and Next Steps
Requirements
- A solid understanding of supply chain or logistics operations.
- Experience using data analysis or business intelligence tools.
- Basic familiarity with programming or scripting.
Audience
- Supply chain analysts.
- Logistics managers.
- Industrial planners.
Testimonials (4)
How to use and explore AI for daily works
Giovani Natalia - PT Astra Honda Motor
Course - AI for Supply Chain and Manufacturing Logistics
real life implementation, very insightful
Olivia Audrey - PT Astra Honda Motor
Course - AI for Supply Chain and Manufacturing Logistics
can learn about ai (colab, n8n)
Jeanny Puspita Sari - PT Astra Honda Motor
Course - AI for Supply Chain and Manufacturing Logistics
How to use & explore AI on daily work