Defect Map

Project Description

Defect Map, a SPC Vision module for defect location

Why is Defect Map needed?

Defect Map is an advanced attribute module of SPC Vision which allows you to easily record and analyze all aspects of visual, surface or attribute inspection. It provides key information to help you control the manufacturing process and focus your improvement efforts

Products containing critical surface or cosmetic features are notoriously difficult to manufacture to consistently high quality standards. This is partly due to the large number of potential causes of the defects but also to the way in which the inspection data is collected and managed.

The combination of the inspection process being very subjective and normally only pass/fail data recorded means it is very difficult to control the process and even harder to improve it.

How can Defect Map help?

By recording details such as defect type, location, severity or size, defect map lets you clearly see the problematic areas, whether a particular defect is getting better or worse and also whether defects are becoming more severe.
This allows you to control the process and focus your improvement efforts.

Key features

  • Electronic ‘measles’ chart
  • Records defect type, size, location & severity
  • Real Time validation & analysis

Typical applications

  • Non destructive testing
  • Composite surface inspection
  • Any products with critical cosmetic features

5 step analysis

  • Reject overview
  • Trend for each defect
  • Focus your efforts
  • Location of worst defects
  • Deeper analysis & action
Learn more


Defect Map – Introducing the concept of defect location and advanced attribute SPC

Defect Map – Introducing the concept of defect location and advanced attribute SPC In the last post we looked at how SPC could be used more effectively for attribute (go/no) characteristics. The key point was that although traditional attribute SPC control charts such as C-charts, NP-charts, P-charts and U-charts  were useful for monitoring changes in the process, the data [...]