Sensitivity Adjustment & Autolearn for Eagle X-Ray

This video will teach you how to adjust the Contaminant Detection functions, or sensitivity, of your Eagle X-ray. We will navigate Simultask using either the touch screen or, optionally, by plugging in a keyboard/mouse to the USB ports on the control panel.

Adjusting Sensitivity

To access the sensitivity settings, we must log into a higher user level. Select ‘Menu,’ ‘User Level,’ and ‘Member of QS.’ Input the QS password and select ‘Login.’ Now, select ‘Back’ to return to the main screen, and then select the ‘Sensitivity’ tab. This is where we start adjustments to the machine sensitivity.

This is a list of the x-ray inspection algorithms, also known as operators. Each operator has a color that will appear on the x-ray image as a tag when it is triggered. Each operator also has a slider that manually adjusts its sensitivity. As the slider is moved to the left towards the 0, the sensitivity is reduced. Moving the slider to the right increases sensitivity.

Each color on the image relates to a color in the sensitivity list. There may be more tags on an image than you can see due to overlapping. To turn off an operator, select the ‘X’ to the left of the operator.

AutoLearn

The AutoLearn Button automatically calibrates some sensitivities—if we give it a little help. Select ‘Auto-learn’ from the bottom of the sensitivity tab. Select ‘Yes’ to begin the auto-learn procedure.

We will need one good example of the product to be run for an autolearn. It must be representative of what you expect a good product to look like during production. If you are running bulk product, a thin bag can be used to maintain the desired product density.

The position of the product will also be important. Please run the autolearn product in positions that are expected to occur during production. For example, if the product is run square-and-centered in the lane all the time, that is the only way you should run it during an autolearn. If a bag of product can be dropped in multiple positions and orientations, please try to provide the machine with examples during your autolearn procedure. Shaking to shift the product, and rotating are good examples of how we can manipulate the autolearn to account for differences between products.

Now we will pass the product through the machine 10 times. There is a counter in the upper-right corner of the screen to tell us how many passes have been made. Once we have run enough passes, select ‘Accept’. This completes the autolearn for contaminants. Not all operators are calibrated by autolearn, but all compatible operators for a single product are calibrated at the same time. AutoLearning is per inspection lane and per product, so you may have to make multiple selections and perform multiple autolearns on multi-lane or automatic product switching machines.