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

Module 1: Fundamentals of AI in Logistics and Supply

• Grasping Artificial Intelligence: key concepts and use cases
• The role of AI in logistics and fuel distribution: opportunities and effects
• No-code AI solutions: Excel AI, ChatGPT, Power BI, and additional tools
• Real-world examples from the transport and fuel sectors

Module 2: Organizing and Interpreting Operational Data

• Recognizing essential logistics and supply datasets (routes, tanks, deliveries)
• Structuring volumetric control and inventory data for AI utilization
• Data refinement, formatting, and verification using Excel
• Generating insights through dynamic tables and pivot charts

Module 3: AI-Driven Forecasting for Fuel Demand

• Comprehending demand forecasting and its influencing factors
• Applying Excel’s AI capabilities and ChatGPT for predictive analysis
• 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 ideal routes and delivery orders
• Utilizing Excel and ChatGPT for route planning under actual constraints
• Practical activity: creating route alternatives for delivery units

Module 5: Cost Analysis and Logistics Improvement

• Identifying cost factors: distance, tolls, fuel usage, and freight
• Estimating logistics expenses through AI models
• Evaluating manual cost planning versus AI-assisted methods
• Developing cost calculation templates with variable inputs

Module 6: Dashboards and KPI Visualization

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

Module 7: Embedding AI in Logistics Processes

• Streamlining repetitive reporting and data aggregation tasks
• Utilizing Power Automate or Excel macros for process automation
• Setting up alert systems for inventory levels or delivery limits
• Real-world example: AI-triggered alerts for tank refill scheduling

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

• Developing a phased AI integration roadmap
• Selecting pilot applications and defining success indicators
• Extending AI-supported workflows across teams
• Promoting ongoing improvement and knowledge exchange practices

Summary and Future Actions