Quality Control Batch Analysis

A Flask-based web application for monitoring and analyzing chemical purity metrics with interactive visualization and statistical quality control analysis.

Overview

This application monitors ethanol purity batches in real-time, calculating rolling averages and control limits using 3-Sigma statistical methods. It provides an interactive web dashboard to visualize production data against quality thresholds.

Features

• Real-time Monitoring: Tracks daily batch purity percentages
• Statistical Analysis: Calculates rolling averages and 3-Sigma lower control limits
• Interactive Dashboard: Visual chart representation of quality metrics
• Quality Status Alerts: Flags batches that fall below control limits as "SYSTEM FAILURE"
• Database Integration: Connects to MySQL for persistent data storage

Project Structure

quality_control_analysis/
├── app.py              # Main Flask application
├── .env                # Environment variables (not in repo)
├── .gitignore          # Git ignore rules
└── README.md           # This file

Requirements

• Python 3.8+
• Flask
• MySQL Connector
• Python-dotenv

Installation

1. Clone or navigate to the project directory

   cd quality_control_analysis

2. Create a virtual environment (recommended)

   python -m venv .venv

3. Activate the virtual environment

   • Windows:

     .venv\Scripts\activate

   • macOS/Linux:

     source .venv/bin/activate

4. Install dependencies

   pip install -r requirements.txt

   Or manually install:

   pip install flask mysql-connector-python python-dotenv

Configuration

Create a .env file in the project root with the following variables:

DB_HOST=your_mysql_host
DB_USER=your_mysql_user
DB_PASSWORD=your_mysql_password
DB_NAME=your_database_name

Database Setup

Ensure your MySQL database contains a chemical_purity table with columns:

• batch_id (INT)
• purity_percentage (FLOAT)
• production_date (DATE)

Running the Application

1. Start the Flask development server

   python app.py

2. Access the dashboard

   • Open your browser and navigate to: http://localhost:5000/

The dashboard will display:

• Blue line: Actual batch purity percentages
• Red dashed line: 3-Sigma lower control limit

How It Works

The application:

1. Connects to MySQL and retrieves chemical purity data
2. Calculates a 7-period rolling average
3. Computes the standard deviation and 3-Sigma lower control limit
4. Marks batches as "STABLE" or "SYSTEM FAILURE" based on control limits
5. Visualizes the data using Chart.js

API Endpoints

• GET / - Returns the interactive quality control dashboard

Technologies Used

• Backend: Flask (Python web framework)
• Database: MySQL
• Frontend: HTML5, Chart.js
• Styling: CSS3

License

This project is for internal quality control monitoring.

Author

Quality Control Analytics Team

Support

For issues or questions, please contact your system administrator.