OneBoxVision Blog

How to specify a web inspection system?

The specification of a vision system for web and sheet operations, is key to a project's success. This article will focus you on the key issues that will help reduce cost of purchase while optimizing performance. The key sections are:

  • 3 key figures that will decide the cost of your inspection system.
  • 5 steps to categorizing defects.
  • The whole is greater than the sum of its parts.
  • 4 results gained from specifying your system correctly.

If you are part of a team that uses, purchases or plans capital expenditure for inspection systems, read more as this framework will add value.

3 Key figures that will decide the cost of your inspection system.

When specifying a web inspection system, there are so many different technologies and issues to consider. Let’s understand some of the critical criteria. The first step to solving any problem is to define the question and to make sure each element of that question is well understood. For a web inspection system, we need to define what we are inspecting. Let’s ask the following questions.

  1. What are the defects that need to be detected? A clear list should be defined. 
    This list should be split according to a Pareto chart. There will be some key defects that represent the majority of the complaints and then a number of outliers. An outlier could be defined as a defect that would be nice to detect but not absolutely necessary.
  2. What are the characteristics and tolerances for each defect class? This includes width, height and contrast.
  3. What are the typical run time speeds for manufacturing? But also record the minimum and maximum speeds?
  4. What are the typical product widths? Also specify the minimum and maximum widths.
  5. What substrates are used? Match the defect list to the substrate. Note the percentage of each substrate used.
  6. Clearly define the installation envelope and the environment.

The goal should be to specify a system for the maximum width, speed and all substrates. Doing so can increase cost of the project considerably. It is important to investigate the cost of a system that will address the key products, defects and requirements and to determine what the delta in cost to address the remainder is. Many projects never get off the ground as a result of over specifying.

The three key factors are:

  1. Line speed – does your line run at 100 mpm or 10 mpm?
  2. Product widths – what is the maximum width of product to run on that line?
  3. Minimum defect size – what is the smallest defect that must be detected?

Let’s create an outline and explain how each element affects the cost and the best practice for specifying a surface inspection system. The system below illustrates a typical line scan application. Assume the web width is 2m and the line speed is 400 mpm. 

Let’s do the calculations. The web width is 2m and speed 400 mpm. The defect catalogue has been calculated and our minimum defect size is 250um.  

The Nyquist principle applies to image processing, so a simple rule of thumb is that the resolution must be at least twice that of the smallest defect. This is not always true as certain lighting techniques can magnify defects. The contrast of a defect to the background also plays a role. However it is a starting point. Please note that detection is not the same as classification. To classify an item, four to five times the resolution is often required.

So for detection, we will need a resolution of 125um in both machine and cross directions as the smallest defect can be a spot so with an equal aspect ratio in both directions.

  • So we need 2000mm/0.125mm = 16000 pixels across the web.
  • The speed of the web is 400 mpm or 6660mm per second so we need cameras that can scan at 6660/0.125 = 54kHz.
  • A good fit will then be four 4k cameras running at 70 kHz. Each camera will have a field of view of 500mm. 
  • Now we have a camera, let’s choose a lens. The length of this sensor is just over 40mm. Each pixel is 10um wide. If we then look at the desired resolution 125 um divided by the size of sensor we can calculated the desired magnification125/10 = 12.5.
  • If we were to use a 50mm lens, the approximate working distance would be 50*12.5 = 625 to the camera sensor. So allow 625mm + 200mm as a vertical envelope.
  • The length of light should be 2.2m allowing an overshoot of 100mm on either side of the web or sheet. The basic specification for this application will then be four 4K line scan cameras running at 70 KHz with a 50mm lens, and a 2.2 m back light.
  • Let’s also consider the same defect specification, but we decided that 90% of the product was not 2m but 1.5m in width and the typical line speed never exceeded 250mpm. The same application could be completed using two 6k cameras running at 40 KHz. This could reduce the cost of such a system by as much as 30%.
  • If width remained at 2m and speed at 400mpm but the minimum defect doubled to 500um, it would also have the same effect. It’s key to understand the effect of these three key criteria.

5 steps to categorizing defects

We looked at the effect of the minimum defect size, width and line speed on the complexity and cost of an inspection system in above. The next step is to analyse the defect suite and to understand how best to catalog and specify for detection. 

    1. Identify all the defects that are present where the machine vision system will be installed. Also include defects that are caused upstream such as substrate issues.
    2. Identify the source of each defect.
    3. Identify the defects that are causing customer complaints, and if possible use a Pareto chart. These are the key targets.
    4. Identify any measurements such as print to edge, or sheet width that if out of specification would result in defective product downstream. 
    5. Categorize according to color and substrate type. 
 

The result should be a table with a list of defects. It's then important to start a collection process so that there is a set of samples that vendors can test. A good practice is to collect A4 or letter size samples of defects. Insert these into plastic covers to protect. Label the plastic cover and clearly identify the defect. It’s crucial you communicate all such information to a vendor. Now you have your defects list.  The next step is for the defect to be categorized according to class and action. The following is an example of how to classify.

 

  • Class 1- Critical defects that must be alarmed immediately and the operator must take action. This may require an alarm to be reset, the machine to stop until the reset is complete. It may also mean placing a physical mark put on the product such as a tag, so that it can be removed downstream prior to shipping.
  • Class 2– Defects that if identified are not an issue unless there is a density of such defects within a time frame or a defined product area. Until then the defect is displayed as a warning, and when the density of that type exceeds a threshold, it is elevated to a class 1 type.
  • Class 3- Small defects that need to be tracked for statistical issues but no action to be taken.

Each defect on the list should be classified. The next step is to assign priority according to returns. There may be a class 1 issue, but if it does occur on all substrates, and what percentage of returns are attributed to this problem. This is a key exercise.
You may ask why?

  • Sometimes one defect class that seems easy for a human to see can define the scale of an automated optical inspection system. Simple examples are very subtle streaks. Large defects that are low contrast can be easily recognized by humans as we can integrate over large areas and can segment these problems. This is not the same for a vision system and may require special processing techniques.
  • Maybe one defect out of a list of ten, may require an extra optical setup such as another bank of cameras and lights.

So the final column needs to be added to the list. This column defines if this defect is detected by system specification A, or A+B, or A+B+C, or by C alone. This will then allow you to allocate your capital where you can best get a return.  So to recap, the steps to complete are:

  1. List of all defects
  2. List of all measurements
  3. List sources of defects
  4. List substrates and colors
  5. List minimum acceptable sizes
  6. Classify according to action
  7. Determine minimum equipment requirements for each defect
  8. Understand which optical setup is required for each defect

4 results that of specifying your system correctly

 Before purchasing a system, think hard on how you will use a system. What are the primary goals?

  1. Stop embarrassing defects getting to your customer.
  2. Increase productivity.
  3. Reduction in substrate waste.
  4. Fault identification so as to enable process improvements.

The overall specification must be reviewed according to these criteria. Make that the output, the hardware and each feature specified brings you closer to meeting these business objectives. If you would like to learn more and read the detailed whitepaper, access the vision library and feel free to download it.

OneBoxVision is a specialist in building solutions for the plastics industry. Contact us and we can provide you with a free consultation or just go ahead and access our vision library to learn more. We provide solutions to industry leaders worldwide and can deliver an out of the box solution that will meet your requirements in weeks.

Access Vision Library ›Contact Us ›

 

Topics: Vision system solutions Building and buying vision systems 100% Inspection OneBox Vision