AI - Supply Chain
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AI in Supply Chain Bootcamp: A 5-Day Exploration of Intelligent Operations
This intensive bootcamp equips professionals in the supply chain domain with the knowledge and skills to leverage Artificial Intelligence (AI) for optimizing operations,improving efficiency, and gaining a competitive edge.
Day 1: Foundations & Landscape ● Demystifying AI in Supply Chain: ○ Understanding key AI concepts and its potential impact on various aspects of supply chain management. ○ Exploring challenges and opportunities addressed by AI across the supply chain (procurement, inventory, logistics, transportation). ○ Discussing ethical considerations and responsible AI practices in supply chain applications. ● Data Landscape & Challenges: ○ Analyzing the vast data generated in supply chains (sensor data, transaction records, logistics data). ○ Highlighting data quality, integration, and accessibility challenges in supply chain data infrastructure. ○ Strategies for overcoming data challenges and preparing data for AI applications.
Day 2: Demand Forecasting & Inventory Optimization ● AI for Demand Forecasting: ○ Leveraging AI for accurate demand forecasting, considering external factors and historical trends. ○ Optimizing inventory levels, reducing stockouts, and minimizing carrying costs. ○ Hands-on: Building basic AI models for demand forecasting using real-world supply chain data. ● AI for Inventory Optimization: ○ Utilizing AI for dynamic inventory allocation, safety stock optimization, and demand-driven replenishment strategies. ○ Implementing AI-powered inventory management systems for real-time visibility and control. ○ Hands-on: Designing an AI-based solution for a specific inventory optimization challenge.
Day 3: Logistics & Transportation Optimization ● AI for Route Optimization & Transportation Planning: ○ Implementing AI for efficient route planning, considering factors like weather, traffic, and vehicle capacity. ○ Optimizing transportation networks, reducing delivery times, and minimizing fuel consumption. ○ Hands-on: Experimenting with AI-powered route optimization tools and simulating scenarios. ● AI for Predictive Maintenance & Fleet Management: ○ Leveraging AI for predictive maintenance of vehicles and equipment, preventing breakdowns and optimizing maintenance schedules. ○ Utilizing AI for real-time fleet tracking, improving visibility and optimizing resource allocation. ○ Hands-on: Building a simple AI model for predicting equipment failures based on sensor data.
Day 4: Procurement & Supplier Management ● AI for Supplier Selection & Risk Management: ○ Applying AI for data-driven supplier selection based on performance, quality, and risk factors. ○ Utilizing AI for automated contract negotiation and managing supplier relationships effectively. ○ Hands-on: Analyzing supplier data and identifying potential risks using AI techniques. ● AI for Fraud Detection & Compliance: ○ Implementing AI for anomaly detection and fraud prevention in procurement processes. ○ Leveraging AI for ensuring compliance with regulations and ethical sourcing practices. ○ Case studies of successful AI-powered solutions for fraud detection and compliance in supply chains. Day 5: Future Trends & Career Exploration ● Emerging Trends & Future Outlook: ○ Exploring cutting-edge AI advancements relevant to supply chain (e.g., explainable AI, blockchain integration). ○ Discussing the future of AI in supply chain and its potential impact on workforce and business models.
AI in Supply Chain Bootcamp: A 5-Day Exploration of Intelligent Operations
This intensive bootcamp equips professionals in the supply chain domain with the knowledge and skills to leverage Artificial Intelligence (AI) for optimizing operations,improving efficiency, and gaining a competitive edge.
Day 1: Foundations & Landscape ● Demystifying AI in Supply Chain: ○ Understanding key AI concepts and its potential impact on various aspects of supply chain management. ○ Exploring challenges and opportunities addressed by AI across the supply chain (procurement, inventory, logistics, transportation). ○ Discussing ethical considerations and responsible AI practices in supply chain applications. ● Data Landscape & Challenges: ○ Analyzing the vast data generated in supply chains (sensor data, transaction records, logistics data). ○ Highlighting data quality, integration, and accessibility challenges in supply chain data infrastructure. ○ Strategies for overcoming data challenges and preparing data for AI applications.
Day 2: Demand Forecasting & Inventory Optimization ● AI for Demand Forecasting: ○ Leveraging AI for accurate demand forecasting, considering external factors and historical trends. ○ Optimizing inventory levels, reducing stockouts, and minimizing carrying costs. ○ Hands-on: Building basic AI models for demand forecasting using real-world supply chain data. ● AI for Inventory Optimization: ○ Utilizing AI for dynamic inventory allocation, safety stock optimization, and demand-driven replenishment strategies. ○ Implementing AI-powered inventory management systems for real-time visibility and control. ○ Hands-on: Designing an AI-based solution for a specific inventory optimization challenge.
Day 3: Logistics & Transportation Optimization ● AI for Route Optimization & Transportation Planning: ○ Implementing AI for efficient route planning, considering factors like weather, traffic, and vehicle capacity. ○ Optimizing transportation networks, reducing delivery times, and minimizing fuel consumption. ○ Hands-on: Experimenting with AI-powered route optimization tools and simulating scenarios. ● AI for Predictive Maintenance & Fleet Management: ○ Leveraging AI for predictive maintenance of vehicles and equipment, preventing breakdowns and optimizing maintenance schedules. ○ Utilizing AI for real-time fleet tracking, improving visibility and optimizing resource allocation. ○ Hands-on: Building a simple AI model for predicting equipment failures based on sensor data.
Day 4: Procurement & Supplier Management ● AI for Supplier Selection & Risk Management: ○ Applying AI for data-driven supplier selection based on performance, quality, and risk factors. ○ Utilizing AI for automated contract negotiation and managing supplier relationships effectively. ○ Hands-on: Analyzing supplier data and identifying potential risks using AI techniques. ● AI for Fraud Detection & Compliance: ○ Implementing AI for anomaly detection and fraud prevention in procurement processes. ○ Leveraging AI for ensuring compliance with regulations and ethical sourcing practices. ○ Case studies of successful AI-powered solutions for fraud detection and compliance in supply chains. Day 5: Future Trends & Career Exploration ● Emerging Trends & Future Outlook: ○ Exploring cutting-edge AI advancements relevant to supply chain (e.g., explainable AI, blockchain integration). ○ Discussing the future of AI in supply chain and its potential impact on workforce and business models.