🏭 Manufacturing Analytics Project

This project showcases an end-to-end Manufacturing Analytics Dashboard built using Excel, Power BI, Tableau, and SQL.
It provides deep insights into production performance, efficiency, and rejection analysis across multiple dimensions.

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📊 Dashboards Included

🔹 Excel Dashboard

• KPIs Tracked:
  • Total Orders
  • Manufactured Quantity
  • Processed Quantity
  • Rejected Quantity
  • Wastage Percentage
• Visual Insights:
  • Monthly Production Trend
  • Top 5 Machine-wise Rejected Quantity
  • Department-wise Manufacture vs % Rejected
  • Employee-wise Rejected Quantity
• Filters:
  • Buyer (H&M, Nike, Uniqlo, Zara)
  • Department (Footwear, Knitwear, Printed Fabric, Woven Labels)
  • Employee-wise data segmentation
• Preview:
  

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🔹 Power BI Dashboard

• Interactive .pbix file for advanced analytics and visual storytelling.
• Designed for dynamic reporting and drill-down insights.
• Preview:
  

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🔹 Tableau Dashboard

• Tableau .twbx dashboard for easy visualization.
• Focus on trend analysis and defect source identification.
• Preview:
  

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🔹 SQL Dataset Preparation

• SQL script (SQL_Manufacture Project.sql) to clean, transform, and prepare raw manufacturing data.
• Ensures data is ready for ingestion into dashboards.

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🚀 How to Use

1. Excel Dashboard

   • Open Manufacture_Final(1).xlsx
   • Link with Manufacturing clean Data.xlsx
   • Use slicers/filters for dynamic insights.

2. SQL Script

   • Run SQL_Manufacture Project.sql in your SQL environment.
   • Generate cleaned and structured tables for dashboards.

3. Power BI / Tableau

   • Open .pbix in Power BI Desktop or .twbx in Tableau.
   • Connect with cleaned dataset for interactive analysis.

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🎯 Key Insights from Dashboards

• Track production efficiency and wastage %.
• Identify top rejected machines and defect sources.
• Compare department-wise performance.
• Analyze employee-level rejection rates.
• Monitor monthly production trends to improve planning.

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🛠️ Tech Stack

• Excel (Pivot Tables, Charts, Slicers, Conditional Formatting)
• Power BI (DAX, Interactive Visuals, KPI Cards)
• Tableau (Visual Analytics, Trend Forecasting)
• SQL (Data Cleaning & Preparation)

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📌 Future Enhancements

• Automate dashboard refresh with live data pipelines.
• Add predictive analytics for forecasting production trends.
• Expand KPIs (cost analysis, downtime tracking, OEE).

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👤 Author

Elluri Imran
📌 GitHub Profile

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✨ This project demonstrates how manufacturing data can be transformed into actionable insights using multiple BI tools.