https://github.com/anand-sony/mttr-dashboard
Streamlit dashboard for MTTR analysis with shift-wise loss insights and machine-level downtime tracking.
https://github.com/anand-sony/mttr-dashboard
analytics business-analytics dashboard data python statistical-analysis
Last synced: 29 days ago
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Streamlit dashboard for MTTR analysis with shift-wise loss insights and machine-level downtime tracking.
- Host: GitHub
- URL: https://github.com/anand-sony/mttr-dashboard
- Owner: Anand-Sony
- Created: 2026-05-01T12:18:40.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2026-05-28T12:07:07.000Z (about 1 month ago)
- Last Synced: 2026-05-28T13:05:09.215Z (about 1 month ago)
- Topics: analytics, business-analytics, dashboard, data, python, statistical-analysis
- Language: Python
- Homepage: https://dkxsds6bfnnebiz4jxkr4j.streamlit.app/
- Size: 243 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
📊 MTTR Analysis Dashboard
Interactive dashboard to track Mean Time To Repair across production lines, machines, and defect categories.
---
## 🚀 Live App
> **[👉 Click here to open the dashboard](https://dkxsds6bfnnebiz4jxkr4j.streamlit.app/)**
No installation needed — runs directly in your browser.
---
## 📋 How to Use
### Step 1 — Open the App
Click the live link above. The dashboard loads instantly.
### Step 2 — Download Sample Data *(Optional)*
Click the **"📥 Download Sample CSV (500 rows)"** button at the top of the app to get a ready-to-use file with the correct format.
### Step 3 — Prepare Your CSV
Your file must have exactly these **7 columns**:
| Column Name | Description | Example |
|---|---|---|
| `Line-ID` | Production line name | `Line-1` |
| `Machine-ID` | Machine name | `Machine-3` |
| `Start-Time` | Breakdown start time | `17-01-2025 06:00` |
| `End-Time` | Breakdown end time | `17-01-2025 08:05` |
| `Category Defect` | Main defect category | `Electrical Defect` |
| `Sub-Category Defect` | Specific defect type | `Relay Contactor` |
| `Down-Time` | Duration in minutes | `99.99` |
> ⚠️ **Date format must be `DD-MM-YYYY HH:MM`**
### Step 4 — Upload & Explore
Upload your CSV and the dashboard will automatically generate all charts.
---
## 📊 Features
| Feature | Description |
|---|---|
| 📈 Pareto Chart by Line | Rank lines by MTTR with cumulative % overlay |
| 🔧 Machine-wise MTTR | Select any line → see machine-level breakdown |
| 🔍 Loss-wise MTTR | Select any machine → drill into defect categories |
| 📋 Top 5 Defects by Line | Most frequent defects per line |
| 🏁 Cross-line Defects | Defects appearing across multiple machines/lines |
| 📥 Export Charts | Download any chart as an interactive HTML file |
---
## 🎛️ Filters
Use the **left sidebar** to:
- Filter by **date range**
- Set a **minimum Down-Time** threshold (e.g. show only breakdowns > 30 min)
---
## 🛠️ Tech Stack
- [Streamlit](https://streamlit.io/) — dashboard framework
- [Pandas](https://pandas.pydata.org/) — data processing
- [Plotly](https://plotly.com/) — interactive charts
- [NumPy](https://numpy.org/) — numerical operations
---
## 📁 Repository Structure
```
MTTR-Dashboard/
├── mttr_dashboard.py # Main dashboard app
├── Sample_Data.csv # Sample dataset (500 rows)
├── requirements.txt # Python dependencies
└── README.md
```
---
## 📬 Contact
Built by **Anand Soni** · [GitHub Profile](https://github.com/Anand-Sony)
## ⭐ Support
## If you found this project useful, consider giving it a ⭐ on GitHub!