OEE Tracker Next-Gen

⚠️ BETA RELEASE ⚠️ This application is currently in Beta and under active development. It is not yet ready for end-user production environments. Features may change, and bugs are expected. Use for testing and evaluation purposes only.

A modern, production-ready Overall Equipment Effectiveness (OEE) tracking application. This project has been migrated from a legacy Streamlit monolith to a fully decoupled architecture featuring a scalable FastAPI backend and a highly dynamic, reactive React frontend.

Architecture

The project is split into two main components:

• Backend (/backend): A RESTful API built with FastAPI and SQLAlchemy. It handles database interactions, complex metrics calculations, anomaly detection, and data ingestion (SCADA, ERP, CSV, Barcode) via strict Pydantic schemas.
• Frontend (/frontend): A modern Single Page Application (SPA) built with React, Vite, and TailwindCSS. It features an advanced dark industrial UI, real-time KPI tracking, and interactive visualizations powered by ApexCharts.

Features

• Live Monitoring Dashboard: Real-time KPI cards (OEE, Availability, Performance, Quality, TEEP), Machine Fleet gauges, and interactive OEE Trend charts.
• Manual Data Entry: A dynamic form for manual shift logging with live OEE preview calculations supporting multiple models (Nakajima, Time Balance, Product Balance).
• Data Ingestion Hub (5-Tab):
  • Excel/CSV Upload: Fuzzy-matching column mapping for bulk shift uploads.
  • SCADA Integration: Automated data extraction pipelines.
  • Barcode/QR Processing: Decode scanner payloads automatically.
  • ERP Sync: Hooks for SAP/ERP system pooling.
  • Import Logs: Detailed views into integration health and anomalies.
• Alerts & Diagnostics: System thresholds to flag TOC (Theory of Constraints) bottlenecks and alert operators to critical downtime anomalies.

Prerequisites

• Python 3.8+
• Node.js 18+ & npm

Setup & Installation

1. Backend Setup

Open a terminal and navigate to the project directory:

cd oee_tracker

Create a virtual environment (recommended) and install the dependencies:

python -m venv venv
# On Windows
venv\Scripts\activate
# On macOS/Linux
source venv/bin/activate

pip install -r requirements.txt

2. Frontend Setup

Open a separate terminal and navigate to the frontend directory:

cd oee_tracker/frontend
npm install

Running the Application

You will need two terminals running concurrently to host both the backend API and the frontend UI.

Start the FastAPI Backend

In your first terminal (with the virtual environment activated):

cd oee_tracker
python -m uvicorn backend.main:app --reload --port 8000

The API will be available at http://127.0.0.1:8000. You can view the automatic Swagger documentation at http://127.0.0.1:8000/docs.

Start the React Frontend

In your second terminal:

cd oee_tracker/frontend
npm run dev

The UI will typically be bound to http://localhost:5173. Open this URL in your browser.

Tech Stack

• Backend: FastAPI, Python, SQLAlchemy, SQLite (Default), Pandas
• Frontend: React, Vite, TailwindCSS (v4 @theme), React Router DOM, ApexCharts, Lucide React (Icons)
• API Communication: Axios