AI ML Project Title
Intelligent Manufacturing Quality Control System
Project Description
What is this project all about
Learn to Build an AI-powered quality control system for tire manufacturing using computer vision and GenAI. This course covers real-time defect detection from production line videos and automated root cause analysis using generative AI. You’ll deploy the solution on AWS, enabling smart monitoring and process optimization. Perfect for professionals aiming to apply AI in industrial automation and smart manufacturing.
Scope: An AI-powered quality control system for tire manufacturing that uses computer vision and GenAI for real-time anomaly detection and automated root cause analysis.
Prerequisites
What You Should Know Before Starting
- Python (Intermediate Level) – You should know how to write functions, use libraries, and fix simple errors.
- Basics of Data Science – Know how to clean, explore, and understand data.
- Machine Learning Basics – Understand what ML is, and how basic models like classification or clustering work.
- Basic Computer Vision – Have an idea of how images are processed using tools like OpenCV.
- Intro to Generative AI – Be aware of how tools like ChatGPT or image generation models generally work.
Tools & Technologies
What Tools & Technologies will be used in this project
- Python – Core programming language for building the entire pipeline.
- YOLOv8 – Pre-trained object detection model for high-accuracy defect detection.
- Transformers (Idefics / LLaMA) – GenAI models used for intelligent analytics/report generation.
- LabelImg or Roboflow – Tools for image annotation and dataset preparation.
- Albumentations – For image data augmentation during model training.
- PyTorch – Deep learning framework for training and fine-tuning custom models.
- Bitsandbytes – For model quantization to reduce model size and inference latency.
- NVIDIA Jetson – Edge device platform for deploying optimized models in real-time.
- Gradio / Streamlit – To build interactive apps that visualize detections and trigger alerts.
- FastAPI or Flask – Backend frameworks to serve inference APIs.
- OpenCV – For image and video stream handling in real-time scenarios.
Learning Objectives
What you will learn in this course
- Capture, annotate, and prepare image datasets for defect detection tasks.
- Fine-tune state-of-the-art models like YOLOv8 or LLaMA on custom tire defect datasets.
- Apply image augmentation techniques to improve model generalization.
- Quantize and optimize models using tools like bitsandbytes for edge deployment.
- Generate inspection reports using GenAI models based on detection outputs.
- Deploy models via API and integrate them into real-time applications using Gradio or Streamlit.
LESSON PLAN
🟦 Module 1: Data Collection & Labeling(1 Hour)
- Capture tyre images and label them
🟦 Module 2: Model Training & Fine-Tuning(1 Hour)
- Use a pre-trained computer vision model (e.g. YOLOv8) or generative AI model (idefics / llama)and fine-tune it on labeled tyre dataset with augmentations to improve defect detection accuracy.
🟦 Module 3: Model Optimization with Quantization(1 Hour)
- Quantize the trained model (e.g. to INT8) using tools like bitsandbytes to reduce size and speed up inference for edge deployment (e.g. NVIDIA Jetson)
🟦 Module 4: GenAI for Analytics(1 Hour)
- Inspection reports from detection results.
🟦 Module 5: Real-Time Deployment & Integration(1 Hour)
- Integrate the optimized model into a API . Use Gradio or Streamlit to process live feeds and trigger alerts for detected defects.
FAQ
This is not just theory. You’ll build a fully working AI-powered IT support automation system — step-by-step, guided by real professionals. It’s practical, project-based, and portfolio-ready.
If you’ve completed some basic programming (especially through our beginner courses), you’re good to go! If not, start with our foundation courses, then return for this project.
Absolutely. You’ll finish with a deployable IT automation project, integrated with GitHub and real-time logging — a great addition to your resume and GitHub portfolio.
It’s beginner-friendly if you’ve completed basic to intermediate programming. If not, take our intro courses first — they’re designed to prepare you for this exact project.
Just install Python, Node.js, and VS Code — we’ll guide you through setup in the first session. Everything else will be covered during the course.
In just 10 focused hours, you’ll learn email automation, GitHub API, WebSocket, and React integration — tools used by real tech teams today.
Yes, you will receive an industry-recognized certificate.
Yes, we specialize in helping businesses find and hire the right talent. Our HR and recruitment services are tailored to meet your company’s specific hiring needs. Contact us to learn how we can support your hiring process.
Please visit our page : WoCons – Custom AI & CAD Solutions | Bengaluru
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