Thus, Dr. Taguchi’s concept of a more realistic Loss Function leads unavoidably to a new definition of world-class quality— “On Target With Minimum Variance.” “On Target” will require that one know the Process Average, and sets the Process Aim in such a way to get the Process Average as close to the Target as possible…
Conformance to Specifications, Zero Defects, Six Sigma Quality, Cost of Quality and all other specification nostrums miss this point. World Class Quality has been defined by “On Target with Minimum Variance” for the past thirty years! The sooner one wakes up to this fact of life, the sooner one can begin to compete.
Wheeler, Dr. Donald J., Chambers, David S. Understanding Statistical Process Control, 2nd Ed. (p. 146)
Statistical theory (theory of probability) as taught in the books for the theory of sampling and theory of distributions applies in the use of random numbers, but not in experiences of life. Once statistical control is established, then a distribution exists, and is predictable.
Deming, W. Edwards. Out of the Crisis (MIT Press) (p. 353). The MIT Press. Kindle Edition.
THE AIM for this post is to share some progress I’ve made enhancing my Taguchi Analyzer proof-of-concept demo since my last post. To recap, I wanted to take Process Behaviour Chart data from my other app, PBC Analyzer Pro, then apply a basic Taguchi Loss Function and fit the results to a curve to see if it could be done. As the app demonstrates, it can.
Building on the knowledge gained from this experiment, it was time to expand the features to dial-in different types of analyses. For this iteration, I decided to use results from some of my past runs of the Red Bead Experiment as this might be more appropriate for a Taguchi application since it deals with defects in lots of materials. As you may recall, the aim of the simulation is to achieve the fewest red beads per shift, ideally 3 or less, so this gives us a nominal value/target to aim the data against. My data set has 216 points gathered from nine real-world iterations, a decent sample size with moderate variation and a few special cause signals. I exported this to Excel for importing into the demo app:
Three Types of Analysis
Next, I added two more loss function types for users to play with to see the different effects on the loss function and how they fit to corresponding curves:
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