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

Module 1: Overview of AI in Logistics and Supply

• Grasping Artificial Intelligence: key concepts and uses
• AI in logistics and fuel distribution: potential benefits and impact
• No-code AI tools: Excel AI, ChatGPT, Power BI, and similar platforms
• Real-world examples from the transport and fuel sectors

Module 2: Organizing and Examining Operational Data

• Recognizing critical logistics and supply datasets (routes, tanks, deliveries)
• Structuring volumetric control and inventory data for AI processing
• Cleaning, formatting, and verifying data in Excel
• Generating insights through dynamic tables and pivot charts

Module 3: AI-Enhanced Fuel Demand Forecasting

• Exploring demand forecasting and its key influencing factors
• Leveraging Excel’s AI capabilities and ChatGPT for predictive analysis
• Projecting short-term (1–2 week) fuel demand patterns
• Practical task: creating a basic forecast model using available data

Module 4: Route Planning and Resource Efficiency

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

Module 5: Cost Analysis and Logistics Improvement

• Identifying cost factors: distance, tolls, fuel usage, freight charges
• Employing AI models to calculate logistics costs
• Evaluating manual versus AI-supported cost planning
• Developing cost calculation templates with variable inputs

Module 6: Dashboards and KPI Representation

• Introduction to Power BI and Excel dashboards
• Designing visual reports for logistics and supply KPIs
• Combining data from volumetric control systems
• Practical session: building a live logistics performance dashboard

Module 7: Embedding AI into Logistics Processes

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

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

• Creating a phased AI rollout strategy
• Selecting pilot projects and defining success indicators
• Expanding AI-supported workflows across teams
• Implementing continuous improvement and knowledge exchange practices

Conclusion and Future Steps