This project presents a Tableau-based analytics dashboard that analyzes manufacturing defects recorded in 2024. It focuses on defect types, severity, repair costs, monthly trends, and the effectiveness of inspection methods to support data-driven quality improvement.
Identify major defect types and severity levels Measure financial impact of defects (repair cost) Analyze monthly defect trends Evaluate inspection methods Provide data-driven recommendations for quality improvement
Source: Kaggle (Public Dataset) This dataset was obtained from Kaggle and is used for academic and portfolio purposes only.
Year: 2024 Metrics: Defect Type, Severity, Repair Cost, Month, Inspection Method
Minor issues occur frequently, indicating process-level mistakes Surface defects dominate, suggesting finishing/handling problems Structural defects are most severe and costly → priority for root-cause analysis Defects show a downward trend from January to June (quality improvement) Manual and visual inspections detect more defects; automation needs enhancement
Cost Reduction: Focus on structural defects first Quality Improvement: Identifies process weaknesses Operational Efficiency: Supports defect prevention strategies Data-Driven Decisions: Enables management to act on insights
Tableau (Dashboard & Visualization) Excel / CSV (Data Source) PowerPoint (Project Presentation)
This Tableau dashboard provides actionable insights into manufacturing defects using 2024 data. It highlights high-impact defect types, compares inspection methods, and visualizes trends that support strategic quality improvements and cost reduction decisions. By presenting defects, severity, repair costs, and monthly variations clearly, the dashboard enables stakeholders to prioritize issues and enhance manufacturing performance.
Pavithra L – MBA (Business Analytics & Finance)