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AI-Digital-Product-Passport

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AI-powered Digital Product Passport platform for intelligent product lifecycle management, predictive maintenance, and sustainability.

Technologies & Skills

Tech Stack: React.js Vite TypeScript Tailwind CSS React Router React Query Axios FastAPI Python Redis SQLAlchemy Alembic JWT Authentication Scikit-learn XGBoost Pandas NumPy Recharts Docker Git
INR 11,800

One-time purchase

What's Included

Complete Source Code
Documentation
Project Report
Presentation Slides
External Download Link

Support & Customization

Support: Basic
Custom modifications not available
File Size 38.75 MB
Last Updated Jul 02, 2026

Resource Links

Purchase this project to unlock source and premium resources. Document/report remain secure preview-based on this page.

AI-Powered Digital Product Passport (DPP) for Smart Manufacturing

The AI-Powered Digital Product Passport (DPP) is an Industry 4.0 platform designed to provide every manufactured product with a secure digital identity, enabling complete lifecycle traceability from raw material sourcing to end-of-life recycling. The platform addresses common manufacturing challenges such as fragmented product data, inefficient traceability, costly product recalls, counterfeit components, and unplanned equipment failures by consolidating all product information into a single intelligent digital passport.

Unlike traditional product tracking systems, our solution integrates Artificial Intelligence, Digital Twin technology, predictive maintenance, and sustainability analytics to deliver real-time insights throughout the product lifecycle. Every product is assigned a unique QR code that allows manufacturers, suppliers, service engineers, distributors, and customers to securely access manufacturing details, quality inspection reports, maintenance history, warranty information, lifecycle events, and environmental impact data through a centralized platform.

The platform leverages machine learning to predict Remaining Useful Life (RUL), estimate failure probability, detect anomalies, and recommend preventive maintenance before equipment failures occur. A Digital Twin provides a virtual representation of each product, enabling continuous monitoring of health, operational status, sensor data, and maintenance activities. Interactive dashboards and analytics help organizations monitor KPIs, manage recalls, improve supply chain visibility, and make data-driven decisions.

To support sustainable manufacturing, the platform tracks carbon footprint, energy consumption, repairability, recyclability, and material usage, helping organizations align with Industry 4.0 principles and circular economy goals. Role-based access control ensures secure access for administrators, manufacturers, suppliers, service engineers, and customers, while executive dashboards, reports, and an AI-powered Copilot provide actionable insights for business users.

Built using React, FastAPI, PostgreSQL, Python, Scikit-learn, XGBoost, Tailwind CSS, Docker, and JWT Authentication, the solution demonstrates how AI-driven Digital Product Passports can improve product transparency, reduce downtime, lower maintenance costs, prevent counterfeit products, accelerate product recalls, and enable smarter, more sustainable manufacturing across industries such as automotive, industrial machinery, aerospace, and electronics.


Future Enhancements


Known Issues


Installation

## 🚀 How to Run the Project


### Method 1: Docker Compose (Recommended)


Make sure Docker is running on your system, then execute:


```bash

# Clone the repository

git clone https://github.com/your-username/AI-Digital-Product-Passport.git

cd AI-Digital-Product-Passport


# Start all backend, frontend, and database containers

docker compose up --build

```


Access Points:

- **Frontend App**: `http://localhost:5173` (or `http://localhost`)

- **Backend API Docs (Swagger)**: `http://localhost:8000/api/docs`

- **Public QR Passport Verification**: `http://localhost:5173/public/passport/1`


---


### Method 2: Manual Local Setup


#### 1. Backend Setup

```bash

cd backend


# Create & activate Python virtual environment

python -m venv venv

# Windows: venv\Scripts\activate | Mac/Linux: source venv/bin/activate


# Install dependencies

pip install -r requirements.txt


# Run database migrations

alembic upgrade head


# Start FastAPI dev server

uvicorn app.main:app --reload --port 8000

```


#### 2. Frontend Setup

```bash

cd frontend


# Install Node modules

npm install


# Start Vite dev server

npm run dev

```


---


## 🔑 Demo Account Credentials


| Role | Email | Password |

| :--- | :--- | :--- |

| **Admin** | `admin@tatatech.com` | `Admin123!` |

| **Customer** | `customer@tatatech.com` | `Customer123!` |

| **Service Engineer** | `engineer@tatatech.com` | `Engineer123!` |

Usage

Step 1: Launch the Application

Start the application using Docker Compose or by manually running the backend and frontend servers. Once the services are running, open the frontend application in your web browser.

Step 2: Login

Use one of the provided demo accounts to access the platform based on your role:

  • Administrator
  • Customer
  • Service Engineer

Each role provides access to different modules and functionalities.

Step 3: Manage Digital Product Passports

Administrators and manufacturers can register new products by entering product details such as serial number, batch number, manufacturer information, and production details. The system automatically generates a unique Digital Product Passport (DPP) along with a QR code for each product.

Step 4: Track Product Lifecycle

View and update the complete lifecycle of each product, including manufacturing, quality inspection, warehousing, shipping, installation, maintenance, repair, and end-of-life recycling.

Step 5: AI Predictive Maintenance

Navigate to the AI dashboard to analyze product health. The system predicts:

  • Remaining Useful Life (RUL)
  • Failure Probability
  • Anomaly Detection
  • Preventive Maintenance Recommendations

Step 6: Digital Twin Monitoring

Open the Digital Twin module to monitor the virtual representation of each product. Users can simulate machine conditions such as temperature, vibration, runtime, and load to observe how these changes affect AI predictions in real time.

Step 7: Sustainability Dashboard

Access ESG analytics to monitor:

  • Carbon Footprint
  • Energy Consumption
  • Recyclability Score
  • Circular Economy Metrics
  • Sustainability Performance

Step 8: AI Copilot

Use the AI Copilot to ask questions in natural language, such as:

  • "Show products requiring maintenance."
  • "Which products have the highest failure risk?"
  • "Display warranty status for Product X."
  • "Generate a sustainability summary."

The assistant retrieves information from the system and provides contextual responses.

Step 9: QR Code Verification

Scan or open the generated QR code to access the public Digital Product Passport. Authorized users can verify product authenticity and view lifecycle history, warranty information, maintenance records, and AI-generated insights.

Step 10: Reports & Analytics

Generate and export detailed reports in PDF format containing product details, AI predictions, lifecycle history, maintenance records, and sustainability analytics for business analysis and compliance purposes.

System Requirements

Hardware Requirements

Minimum

  • Processor: Intel Core i3 (8th Gen) / AMD Ryzen 3 or equivalent
  • RAM: 8 GB
  • Storage: 10 GB free disk space
  • Display: 1366 × 768 resolution
  • Internet: Required for dependency installation and updates

Recommended

  • Processor: Intel Core i5 (10th Gen) / AMD Ryzen 5 or higher
  • RAM: 16 GB or more
  • Storage: 20 GB SSD free space
  • Graphics: Integrated GPU or higher (for smoother Digital Twin animations)
  • Internet: High-speed broadband connection

Software Requirements

Operating System

  • Windows 10/11 (64-bit)
  • Ubuntu 20.04+ / Debian-based Linux
  • macOS Monterey or later


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