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

Module 1: Fundamentals of AI in Logistics and Supply

• Exploring Artificial Intelligence: core concepts and practical applications
• The role of AI in logistics and fuel distribution: potential benefits and impact
• Introduction to no-code AI solutions: Excel AI capabilities, ChatGPT, Power BI, and more
• Real-world examples from the transportation and fuel industries

Module 2: Organizing and Analyzing Operational Data

• Pinpointing critical logistics and supply datasets, including routes, tanks, and delivery records
• Preparing volumetric control and inventory data for AI processing
• Data cleansing, formatting, and validation techniques in Excel
• Generating insights through dynamic tables and pivot charts

Module 3: AI-Driven Forecasting for Fuel Demand

• Understanding demand forecasting and the variables that influence it
• Leveraging Excel’s AI features and ChatGPT for predictive analysis
• Projecting 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 to plan routes with specific real-world constraints
• Hands-on activity: generating route options for delivery units

Module 5: Cost Estimation and Logistics Optimization

• Identifying primary cost factors: distance, tolls, fuel consumption, and freight charges
• Utilizing AI models to predict logistics costs
• Evaluating manual planning versus AI-assisted cost strategies
• Developing cost calculation templates with dynamic input fields

Module 6: Dashboards and KPI Visualization

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

Module 7: Integrating AI into Logistics Workflows

• Automating routine reporting and data aggregation tasks
• Utilizing Power Automate or Excel macros for process automation
• Setting up alert systems for inventory levels and delivery milestones
• Practical example: implementing AI-based alerts for tank refill scheduling

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

• Constructing a phased AI implementation roadmap
• Defining pilot use cases and establishing success metrics
• Expanding AI-assisted workflows across various teams
• Cultivating a culture of continuous improvement and knowledge sharing

Course Summary and Recommended Next Steps