Vision systems provide peace of mind when it comes to production quality but they can also generate valuable data that tracks process variability. Diving into the world of vision data can seem overwhelming, but with the right tips and tricks you can set up a system to work for you.

Real-life quality problems are conundrums. Dorian Shainin realized that recognizing the distinctive characteristics of a problem was critical. He also knew that applying the right tactics was the key to the solution; however, many of the analysis tools of his time were not effective.

I recently attended a lecture by an industrial statistician. Part of the lecture included a summary of Dorian Shainin’s body of work. I had to smile as the lecturer spoke about Shainin’s “exaggerated claims” of the results attributed to his methods and his infamous “pre-control.” 

Many statistical analyses and p-values assume that your data follow a normal distribution. However, normally distributed data isn’t always the norm. So, what’s a good data analyst to do?

The scope of product testing is growing broader and more complex. Traditionally, the objective was to confirm compliance with relevant safety regulations. But today we’re seeing more product management teams also push for functionality and reliability testing. 

In his book, “Fooled by Randomness,” celebrated author Nassim Nicholas Taleb says, “This high-yield market resembles a nap on a railway track.