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

Module 1: Introduction to AI in Logistics and Supply

• Exploring Artificial Intelligence: key concepts and practical uses
• The role of AI in logistics and fuel distribution: opportunities and impact
• Overview of no-code AI tools: Excel AI, ChatGPT, Power BI, and others
• Real-world examples from the transportation and fuel industry

Module 2: Structuring and Analyzing Operational Data

• Identifying critical logistics and supply datasets (routes, tanks, deliveries)
• Organizing volumetric control and inventory data for AI integration
• Data cleaning, formatting, and validation processes in Excel
• Building dynamic tables and pivot charts to generate insights

Module 3: AI-Assisted Forecasting for Fuel Demand

• Understanding demand forecasting and the variables that influence it
• Utilizing Excel’s AI capabilities and ChatGPT for predictive analysis
• Forecasting short-term (1–2 week) fuel demand trends
• Practical exercise: creating a simple forecast model using existing data

Module 4: Route Planning and Resource Optimization

• Core principles of route optimization and scheduling
• Employing AI tools to recommend optimal routes and delivery sequences
• Applying Excel and ChatGPT for route planning within real-world constraints
• Hands-on activity: generating route options for delivery units

Module 5: Cost Estimation and Logistics Optimization

• Identifying key cost factors: distance, tolls, fuel consumption, freight
• Using AI models to project logistics costs
• Comparing manual cost planning with AI-assisted methods
• Developing cost calculation templates with dynamic inputs

Module 6: Dashboards and KPI Visualization

• Getting started with Power BI and Excel dashboards
• Designing visual reports for logistics and supply KPIs
• Integrating data from volumetric control systems
• Hands-on: building a real-time logistics performance dashboard

Module 7: Integrating AI into Logistics Workflows

• Automating repetitive reporting and data consolidation tasks
• Using Power Automate or Excel macros for task automation
• Setting up alert systems for inventory or delivery thresholds
• Practical example: AI-based alerts for tank refill scheduling

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

• Constructing a step-by-step AI implementation roadmap
• Selecting pilot use cases and defining success metrics
• Expanding AI-assisted workflows across teams
• Fostering continuous improvement and knowledge-sharing practices

Summary and Next Steps