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: core concepts and practical uses
• The role of AI in logistics and fuel distribution: potential benefits and impact
• Overview of no-code AI tools: Excel AI, ChatGPT, Power BI, and others
• Real-world examples from the transportation and fuel industries

Module 2: Structuring and Analyzing Operational Data

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

Module 3: AI-Assisted Forecasting for Fuel Demand

• Understanding demand forecasting and key influencing factors
• Utilizing Excel’s AI capabilities and ChatGPT for predictive analysis
• Predicting short-term (1–2 week) fuel demand trends
• Practical exercise: constructing a basic forecast model using existing data

Module 4: Route Planning and Resource Optimization

• Key principles of route optimization and scheduling
• Using AI tools to recommend optimal routes and delivery sequences
• Applying Excel and ChatGPT for route planning under real-world constraints
• Hands-on activity: generating route alternatives for delivery units

Module 5: Cost Estimation and Logistics Optimization

• Recognizing cost drivers: distance, tolls, fuel consumption, and freight
• Employing AI models to calculate logistics costs
• Comparing manual planning methods with AI-assisted cost planning
• Developing cost calculation templates with dynamic input fields

Module 6: Dashboards and KPI Visualization

• Introduction to Power BI and Excel-based dashboards
• Designing visual reports for logistics and supply KPIs
• Integrating data from volumetric control systems
• Hands-on session: creating a real-time logistics performance dashboard

Module 7: Integrating AI into Logistics Workflows

• Automating routine reporting and data consolidation tasks
• Using Power Automate or Excel macros for task automation
• Setting up alert systems for inventory levels or delivery thresholds
• Practical example: implementing an AI-based alert system 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
• Scaling AI-assisted workflows across different teams
• Establishing practices for continuous improvement and knowledge sharing

Summary and Next Steps