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 becomes much more useful when additional information is added.

We will  now look at this in more detail.  Throughout this post, I will make reference to ‘Defect Map’.  Defect Map is a advanced attribute module  SPC Vision software made by Infodream.  It was developed with help from our industrial partners specifically for applications with a large number of complex attribute features (carbon composite components).  The purpose of this blog is not however to directly promote our software but to demonstrate how the methods can be deployed to great effect.

So, as previously outlined,  traditional attribute SPC has some limitations and one of them is the lack of information recorded about the defect.  Although we can monitor the defect quantities and trend, we know little else about the defect to help us understand the root cause and rectify it.

The first step forward is to categorise the failures into ‘defect types’ e.g. scratches, pits, dents etc. We can then use Pareto analysis to determine which defects are occurring most often and prioritise our improvement activities.

However, this information may still not be adequate and further detailed defect information is needed in order  to:

  1. For high value products, detailed defect information is usually required in order to decide the final disposition of a part.  i.e. scrap,  repair or conditionally accept.
  2. For process improvement, knowing the defect ‘type’ is only the first step in understanding the root cause – further in-depth analysis is required.

This detailed information is often not recorded at the time when the defect is found and is collected at a later date (Sometimes the request for the data may be weeks).  This has negative consequences including disrupted production schedules and delayed root cause analysis and action ( further defects may also have occurred during this ‘waiting period’)

Often, the additional defect information requested in order to process the defective part focuses on:

  • Location of the defect on the product
  • Severity of the defect

This may seem rather obvious, but in many applications, this type of information is not collected as standard practice.

Defect Location Mapping

Therefore, we should first introduce the notion of ‘defect location’ for attribute data collection. (Think about a ‘measles chart’ where the position of each defect is marked on a drawing of the part) So, instead of recording only the presence of the defect, we will also document where it is located on the part.

Short term Defect map (for single piece)

The image above shows an example of  a simple ‘defect map’.  Each of the boxes represents a zone of the car.  The red boxes indicate the presence of a defect and the number inside the box indicates the number of defects in that zone.

We can imagine a variety of industrial applications where it is important to understand the position of a defect in order to make a decision on the part.
For example, in an aerospace application, a defect  in a zone of low physical stress might be acceptable whereas the same defect in a high stress zone would not be acceptable .

For a manufacturer of watches, a scratch can be accepted if the scratch is in a non- visible part of the final piece. Conversely, if the scratch is in a highly visible area of the watch, it would not be acceptable.

The examples above highlight where the location of a defect plays a key role in the decision making process. But, just as importantly the defect location also provides key information to help us determine the root cause of the problem.  This data is especially useful, when the defect map (measles chart) is not just for a single part but  a record over a number of parts. In this way, we get a long terms view of where on the product defects are most often occurring.

Long Term Defect map (for multiple pieces)

In the above example, we can clearly see the problematic areas of the car are the front right hand wing (fender) and the rear boot (trunk).

This cumulative defect location information could also be viewed using a Pareto chart.

The next example is for a large composite panel where the zones (locations) are defined with respect to the intersection of the ribs and stringers. In this case the map is displayed not as a picture but using a spreadsheet.

Example of DMAP with defects on composite panel. (long term over 20 pieces)

With the help of Defect Map, we can easily identify areas which often have defects, and really narrow down the scope of the root cause investigations.

Defect Severity

The second key piece of missing information most often required concerns the severity of the defect.  i.e. additional defect information such  size, length, depth, surface area etc. This is also very important information for decision making.

The severity of the defect can be recorded either as a variable value (e.g. measured length, depth, area etc) or could be classified attribute (e.g. minor, major, critical etc)

Again, this information may not be recorded at the time when the defect was found but may be requested at a later date when a decision must be made about the final disposition.  This is often the case when a defect occurs on high value complex parts where it is very expensive to scrap the part.  In such situations, engineers must make the call and detailed information is usually required.

For example, in some areas (zones) of the part, a crack can be considered acceptable if its length is smaller than 4mm. If it is larger, the part should be scrapped . In other zones, zero cracks are allowed.  To complicate matters further, sometimes even a crack longer than 4mm may be allowable but only after approval.  Therefore, having this additional information at hand can drastically reduce time taken to process the non-conforming product.

The example below shows both the defect location and defect size (categorised attribute) being recorded for a defect type ‘crack’

DMAP example showing defect size data input.

DMAP example showing surface area of de-lamination defects

Detailed analysis can also be done on the ‘severity’ data to further understand the defect,  potential causes, trends etc.


As  illustrated in the above examples, recording additional information with attribute defects can really add value to the inspection process.

  1. Speeds up  root cause analysis for process improvement activities
  2. Reduce production disruption by quickly providing  the  detailed information required  to decide the final disposition of  defective product.

The additional information required  relates to:

  • Defect type (what is the problem)
  • Defect Location (where is the problem)
  • Defect Severity (how big is the problem)

We  can combine:

  • Traditional attribute SPC charts to monitor overall defect trends
  • Location and Severity information
  • Graphical analysis

This combination provides a powerful tool for process improvement and efficient management of defects.

As mentioned at the beginning, the purpose of this blog is not to directly promote SPC Vision ‘Defect Map’.  However, to get the benefits of the methods discussed,  a paper based system would be far too labour intensive and slow to provide real time benefits.  Therefore,  the results can only really be achieved using a software based system.

Frédéric Henrionnet
Operation Director, Infodream

Andreas Völker
Product Manager, Infodream

Sources :
– Attribute  Module for SPC Vision software
Defect Map module  for SPC Vision software
– The screenshots were done using the software: Defect Map

Learn more about Defect Map

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