Quality Inspection Analytics in iVendNext: Data-Driven Quality Control

Quality Inspection Analytics in iVendNext: Data-Driven Quality Control

1. Overview

This article gives you an overview of how Quality Inspection Analytics helps retailers interpret inspection data and convert it into clear, actionable insights by:
Identifying recurring defects
Tracking supplier and customer quality trends
Optimizing inspection processes




2. Core Analytical Features

2.1 Quality Inspection Summary Report

Access: Home > Manufacturing > Reports > Quality Inspection Summary


Key Metrics:

  • Acceptance/Rejection rates by:

    • Item

    • Supplier

    • Inspector

    • Time period


2.2 Defect Pareto Analysis

What It Shows:

  • Top 5 defect types (e.g., "Dimensional Errors - 42%")

  • Helps prioritize corrective actions


2.3 Trend Analysis

Track Over Time:

  • Monthly rejection rate trends

  • Seasonal quality variations




3. Advanced Analytics Techniques

3.1 Custom Report Builder

Create ad-hoc reports with:
Drag-and-drop fields (Item, Batch, Inspector)
Filters (Date ranges, Status)
Visualizations (Bar charts, Trend lines)


3.2 Supplier Performance Dashboard

Monitor:


  • On-time inspection completion

  • First-pass yield rates

  • Comparative analysis across suppliers


3.3 Cost of Quality (CoQ) Analysis

Calculate:


CoQ = (Rejected Qty × Unit Cost) + Rework Costs  




4. Step-by-Step: Generating Insights

4.1 Accessing Standard Reports

  1. Go to: Home > Manufacturing > Reports

  2. Select:

    • Quality Inspection Summary

    • Defect Analysis Report

  3. Set filters → Generate


4.2 Creating Custom Views

  1. Click "Customize" on any report

  2. Add/remove columns → Save as "My Inspection View"


4.3 Exporting Data

  • Formats: Excel, PDF

  • Automate: Schedule email delivery




5. Case Study: Reducing Defects by 30% in Apparel Stitching 


Problem: 

High rejection rate for Men’s Formal Shirts due to stitching inconsistencies


Analytics Approach:

Analyzed defect patterns across batches and found that 47% of stitching defects originated from Supplier Y.


Root Cause:

Inconsistent needle calibration and thread tension settings on Supplier Y’s machines.


Action:

Updated the inspection checklist to include thread tension and needle calibration checks AND Conducted a hands-on training session for Supplier Y’s tailoring unit on machine setup best practices.


Result: 

Defect rate dropped from 18% to under 6% within 3 months, improving delivery timelines and reducing rework costs.




6. Troubleshooting

Here’s a quick look at some common issues you might run into.


Issue

Solution

Missing inspection data

Check user permissions & mandatory fields

Inconsistent trends

Verify timezone settings in reports

Slow report loading

Optimize with fewer concurrent filters




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