Smart_Manufacturing_Unit1_Part2_PPT.pptx

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1. Smart Manufacturing – Unit 1 (Part 2) Implementing Smart Manufacturing Across an Industry Course: 22EI011 – Smart Manufacturing

2. Overview Smart manufacturing integrates suppliers, production, logistics, and customers into a connected, data-driven value chain.

3. Assessment and Planning • Evaluate existing infrastructure • Identify digital readiness • Define short- and long-term goals • Choose scalable, compatible technologies

4. Digital Infrastructure Development • Sensor integration for various parameters • Use of industrial IoT protocols • Edge computing for real-time processing • Cloud for storage and analytics

5. Data Collection and Management • Use DAQs to collect sensor data • Store in data lakes/warehouses • Implement cybersecurity measures

6. Analytics and Decision-Making • Apply AI/ML to analyze data • Predict failures and optimize inventory • Use dashboards for real-time insights

7. Automation and Control • Upgrade with PLCs and industrial PCs • Use robots/cobots • Implement closed-loop feedback systems

8. Workforce Development • Train in smart tools and collaboration • Upskill via certifications • Promote interdisciplinary teamwork

9. Supply Chain and Customer Integration • Use shared platforms for visibility • Track using RFID and blockchain • Enable mass customization

10. Example – Automotive Industry • Real-time part tracking • Robotic inspection systems • Predictive maintenance • Inventory alerts • Feedback-based design improvements

11. Benefits of Industry-Wide Implementation • Improved efficiency & reduced rework • End-to-end visibility • Agile and adaptive manufacturing • Sustainable practices • Customer-centric personalized production

12. Discussion Questions 1. Why is real-time monitoring essential for smart manufacturing? 2. What are challenges in transitioning from traditional methods? 3. How can predictive analytics improve factory efficiency?