📊 Streamlit OEE Dashboard

A multi-page Streamlit dashboard designed for monitoring operational performance through key industrial metrics such as OEE (Overall Equipment Effectiveness), productivity, and working hours. The application includes authentication, role-based access, and interactive analytics powered by an Excel data source.

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🚀 Features

🔐 Authentication System

• Login page with multi-role support
• Role-based access control (customizable)
• Secure session handling
• Logout functionality

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📈 Dashboard Pages

1. OEE Overview

• Displays key OEE KPIs
• Interactive visualizations
• Performance breakdown (Availability, Performance, Quality)

2. Hours Analysis

• KPIs related to working hours
• Graphs for time distribution and trends
• Useful for identifying inefficiencies in time usage

3. Productivity Analysis

• Productivity-focused KPIs
• Comparative and trend-based charts
• Helps evaluate operational output

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📅 Date Filtering

• Available across all dashboard pages

• Select:

  • A specific month
  • Or aggregate across all months

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📬 Send Email

• Built-in distribution form (currently in work)
• Includes CAPTCHA verification
• Configurable to send messages using your own Gmail account

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📂 Data Source

• Uses an Excel file as the database
• Easy to update and maintain without needing a full database system

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🛠️ Tech Stack

• Python
• Streamlit
• Pandas
• Plotly / Matplotlib (depending on implementation)
• OpenPyXL (Excel handling)

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📦 Installation

1. Clone the repository

git clone https://github.com/jalfr3d/streamlit-dashboard-oee.git

2. Create virtual environment (recommended)

python -m venv .venv
source .venv/Scripts/activate  # Windows
# or
source .venv/bin/activate      # macOS/Linux

3. Install dependencies

pip install -r requirements.txt

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▶️ Running the App

streamlit run app.py

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⚙️ Configuration

📧 Gmail Setup (for Contact Form)

To enable email sending:

1. Use a Gmail account
2. Enable App Passwords (recommended)
3. Add credentials to your environment variables or config file:

sender = os.getenv("GMAIL_SENDER")
secret = os.getenv("APP_PASS_GMAIL")
recipient = os.getenv("RECIPIENT_EMAIL")

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📊 Excel Data

• Place your Excel file in the project directory
• Ensure it follows the expected schema (columns used by the dashboard)
• Update file path in the code if needed

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🔐 Roles Configuration

• Roles can be defined in:

  • A config file
  • Hardcoded dictionary
  • External source (optional)

Example:

users = {
    "admin": {"password": "1234", "role": "admin"},
    "user": {"password": "abcd", "role": "viewer"}
}

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📁 Project Structure

├── app.py
├── DataBaseProduction.xlsx
├── users.json
├── images/
|   └── logo.jpg
├── pages/
│   ├── account.py
│   ├── contact.py
│   ├── hours.py
|   ├── oee.py
│   └── productivity.py
├── utils/
│   ├── auth.py│   
│   └── data_loader.py
├── requirements.txt
└── README.md

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🧩 Notes

• The app is designed to be modular and extensible
• Excel-based backend makes it easy to prototype and deploy quickly
• Suitable for internal dashboards or lightweight analytics tools

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📌 Future Improvements

• Replace Excel with SQL database
• Add user registration system
• Improve role granularity
• Deploy to cloud (Streamlit Cloud / AWS / Azure)

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👨‍💻 Author

Developed as a custom Streamlit analytics solution.

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📄 License

This project is open-source and available under the MIT License.