“By controlling the important variables, dimensional changes in heat treatment can be controlled.” Patrick McKenna
Variability is the enemy in our precision machining shops, and reducing variability is a key to sustaining our businesses and improving our capabilities.
When I talk about statistical process control with someone,  I listen closely to see if they are focused on the average (where the process is performing) or the standard deviation ( how the process is performing.)
If they are fixated on the average, I know I need to look at the data myself.  On the other hand if they are talking about standard deviations, I generally take their word on the data…
In the latest  issue of Production Machining Magazine, PMPA Technical Member Patrick McKenna from Nevada Heat Treating Inc., and Daniel Herring, the Herring Group Inc.  teach a nice class on how to reduce process variation in heat treat to minimize the post heat treat variability that all of us face.

Good advice here...

This is important if we are not to waste our production time trying to remove excess material because we left too much stock  for cleanup, or worse, finding the parts have shrunk in some critical dimension, rendering all of the parts ‘scrap.’
This article lists 9 variables NOT in control of the heat treater, and 14 that are under their control (furnace temperature uniformity, load configuration) or shared by the customer ( process selected, batch size, part size).
Not every order we produce is part of a long running job where we can control every input variable, but this piece does a great job of providing sensemaking on what can be a complicated and confusing subject.
I predict that you’ll keep this article in your “great to know” file.

I’m really more focused on Quality.
On draining the swamp, not swamp beautification.
Quality Assurance.
Organizational Improvement. (People and Processes.)
Lean is just another way of saying eliminate waste.
Six Sigma uses statistical jargon, but how many people in top management can even get close to describing the area under the normal curve at +/- 3 sigma? Or know that a sigma is a standard deviation? And what that means?
Let alone recognize non-normal data?
(“Six Sigma” is just another term for “Magic ” to the guys wearing ties at the OEM’s…)
I’m not into cute names for serious tools. We were using  powerful  statistical techniques before they got new cute  names and became safe  Okay fashionable  to say up in the carpeted front office.

Draining the swamp doesn't need tools with cute names.

However, if you are serious about Quality. Quality Assurance. Organizational Improvement. And Tools You Can Use to drain the swamp, instead of reading crap of unknown provenance from the web,  here’s your reading list:
1) Competing Against Time by Stalk and Hout
2) Toyota Way by Jeffrey Liker.Frankly, if you haven’t already read
3) The Goal, by Eliyahu Goldratt, (get this one first it will give you key insight into how to think about manufacturing.)
4) The Machine That Changed The World by Womack is also worth your time.
Take these tools, and love it.
Excavator photo credit.