AI for Logistics and Supply: Practical No-Code Applications for the Fuel Industry Training Course

Module 1: Introduction to AI in Logistics and Supply

• Grasping Artificial Intelligence: key concepts and practical uses
• The role of AI in logistics and fuel distribution: potential benefits and impact
• No-code AI solutions: Excel AI capabilities, ChatGPT, Power BI, and other platforms
• Real-world examples from the transport and fuel sectors

Module 2: Organizing and Analyzing Operational Data

• Recognizing critical logistics and supply datasets (including routes, tanks, and deliveries)
• Structuring volumetric control and inventory records for AI processing
• Data cleansing, formatting, and verification using Excel
• Generating insights through dynamic tables and pivot charts

Module 3: AI-Supported Forecasting for Fuel Demand

• Explaining demand forecasting and its key influencing factors
• Leveraging Excel’s AI features and ChatGPT for predictive analytics
• Predicting short-term (1–2 week) fuel demand patterns
• Practical task: constructing a basic forecast model using available data

Module 4: Route Planning and Resource Optimization

• Core principles of route optimization and scheduling
• Employing AI tools to recommend optimal routes and delivery orders
• Using Excel and ChatGPT for route planning under specific constraints
• Practical exercise: generating route alternatives for delivery vehicles

Module 5: Cost Estimation and Logistics Efficiency

• Pinpointing cost factors: distance, tolls, fuel usage, and freight charges
• Applying AI models to project logistics expenses
• Contrasting manual vs. AI-assisted cost planning approaches
• Developing cost calculation templates with dynamic parameters

Module 6: Dashboards and KPI Visualization

• Overview of Power BI and Excel dashboard capabilities
• Creating visual reports for logistics and supply KPIs
• Integrating data from volumetric monitoring systems
• Practical session: building a live logistics performance dashboard

Module 7: Embedding AI into Logistics Workflows

• Automating routine reporting and data aggregation tasks
• Utilizing Power Automate or Excel macros for workflow automation
• Setting up alert systems for inventory levels or delivery milestones
• Practical case: AI-driven alerts for tank refilling schedules

Module 8: 90-Day AI Adoption Strategy for Logistics and Supply

• Crafting a phased AI implementation roadmap
• Selecting pilot scenarios and defining success indicators
• Expanding AI-supported processes across teams
• Fostering continuous improvement and knowledge exchange practices

Recap and Future Directions