AI in Manufacturing
Build. Automate. Improve.
Course Objective
This course is designed to equip manufacturing managers, supervisors, entrepreneurs, and shop-floor teams with practical AI tools to improve operations, minimize downtime, enhance product quality, reduce waste, and improve workforce safety — without requiring coding or advanced technical knowledge.
By the end of this course, participants will:
• Be able to use no-code AI platforms to solve common factory challenges.
• Automate repetitive tasks like reporting, inventory alerts, and quality checks.
• Build and deploy simple AI solutions for real-world manufacturing problems.
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Module 1:
Understanding AI for Everyday Manufacturing
- Topics:
- What is AI? (Explained using real-life analogies like Alexa, Netflix, Google Maps)
- Introduction to AI in manufacturing: where it is already used (e.g., BMW, Tesla, SMEs).
- Pain points in factories: machine failures, late deliveries, stock mismanagement.
- Tools covered: ChatGPT (for data insights), Microsoft Lobe (drag-and-drop AI models).
- Hands-on: Create your first simple AI model (e.g., image sorting).
Module 2:
Predictive Maintenance Made Simple
- Problem Solved: Machine breakdowns causing costly downtime
- Topics:
- AI-powered maintenance – how it predicts failures before they happen.
- Real-world case studies (e.g., predictive alerts at Toyota & Siemens).
- Tool: AWS Lookout for Equipment – no coding, just uploading machine log data.
- Hands-on: Predict a machine’s maintenance schedule using sample data.
Module 3:
Quality Control with AI (Visual Inspection)
- Problem Solved: Manual inspection errors.
- Topics:
- How computer vision works – explained simply.
- Using cameras + AI to detect defects in real-time.
- Tools: Microsoft Lobe, Roboflow (upload, train, test – no code).
- Hands-on:
- Upload 10 product images (good vs. defective) and train a simple defect detection model.
Module 4:
AI for Inventory & Supply Chain Optimization
- Problem Solved: Overstocking or shortages.
- Topics:
- How AI forecasts demand (like how Amazon predicts your next purchase).
- Linking AI with inventory data to auto-generate purchase alerts.
- Tools: Google AutoML, Excel-based AI add-ons.
- Hands-on:
- Build a smart Excel sheet that predicts next month’s inventory needs.
Module 5:
Automating Repetitive Tasks (No-Code RPA)
- Problem Solved: Daily manual data entry and reporting.
- Topics:
- What is RPA? (Robotic Process Automation explained).
- Automating order tracking, generating daily production reports.
- Tools: Zapier, Make.com (drag-and-drop workflows).
- Hands-on:
- Build a flow to automatically email daily production summaries.
Module 6:
Energy & Cost Optimization
- Problem Solved: High power costs and wastage.
- Topics:
- AI for energy saving – real-world case studies.
- AI dashboards for power consumption monitoring.
- Tools: Siemens MindSphere (trial version), IBM Watson IoT.
- Hands-on: Create a simple energy monitoring dashboard.
Module 7:
AI for Workforce Safety & Monitoring
- Problem Solved: Unsafe practices and accidents.
- Topics:
- How AI + CCTV cameras monitor safety zones.
- Tool: Google Teachable Machine – create custom safety alerts.
- Hands-on:
- Train an AI to detect unsafe helmet-less workers using sample images.
Module 8:
Ethics, Safety & Regulatory Compliance
- Each participant selects a real-life problem (e.g., frequent breakdowns, inspection delays).
- Using learned AI tools, they build a basic working AI solution (predictive model, automated alert, or dashboard).
- Final Presentation: Showcase the AI solution to mentors.
Learning Tools & Platforms Used
- AI Tools: Microsoft Lobe, Google Teachable Machine, Roboflow, Google AutoML, AWS Lookout for Equipment.
- Automation Tools: Make.com, Zapier, Power Automate.
- Visualization: Power BI, Google Data Studio (for dashboards).
- IoT/Industrial Tools: Siemens MindSphere (trial), IBM Watson IoT.
📈 Learning Outcomes
By the end of this course, learners will:
- Understand AI basics in simple language – no coding or complex theory.
- Use AI tools to predict machine breakdowns and schedule maintenance.
- Build a visual defect detection system using only images.
- Automate reporting, alerts, and inventory planning without IT teams.
- Monitor energy consumption and reduce costs.
- Create AI models to ensure worker safety with live alerts.
- Develop a real-world capstone project that solves a manufacturing issue.
- Gain confidence to implement AI solutions independently.
Duration:
| Section | Details |
| Total Duration | 8 Weeks (Flexible) |
| Weekly Commitment | 5–6 hrs |
| Delivery Mode: | Online (Video + Live sessions + Labs) |
| Capstone Project: | Real-world mobility solution using AI |