In the February issue of Quality Digest, Joseph M. Juran pointed out that quality needs to “scale up” if it is to remain a viable force in the next...
Read more
06Mar
Non-Normal Distributions in the Real World
One day, early in my quality career, I was approached by my friend Wayne, the manager of our galvanizing plant. ‘Tom,” he began, “I’ve really been pushing quality in...
Read more
06Mar
How Do I Compute sigma? Let Me Count the Ways.
With SPC work, we normally try to analyze a process distribution’s shape, central tendency and spread. We usually measure this last item by computing an estimate of the process...
Read more
06Mar
Applying Virtual DOE in the Real World
In last month’s column I presented a method for conducting virtual design of experiments (VDOE) using artificial neural networks and data mining. This month I will present a manufacturing...
Read more
06Mar
Selecting Winning Project Portfolios
In a previous column I discussed how Six Sigma projects should be selected using the theory of constraints (TOC). After attempting to do so, most discover yet another constraint:...
Read more
06Mar
DMAIC and Project Plans
Six Sigma’s magic doesn’t lie in statistical or high-tech razzle-dazzle. Six Sigma relies on tried-and-true methods that have been around for decades. In fact, Six Sigma discards a great...
Read more
06Mar
Divide and Conquer
A typical Six Sigma project adds between $145,000 and $250,000 to the bottom line. These numbers provide useful guidelines to the Black Belt for breaking the project down to...
Read more
06Mar
Defining Six Sigma Projects
Six Sigma’s impressive bottom-line results normally flow from Six Sigma projects. Properly defined Six Sigma projects meet certain criteria: Six Sigma Criteria They have clearly defined deliverables. They are...
Read more
06Mar
Why Six Sigma Is Not Enough
Some people, including me, believe that garden variety Six Sigma doesn’t go far enough. In fact, even zero defects falls short. Defining quality as only the lack of nonconforming...
Read more
06Mar
The Six Sigma Management Paradox
Simply stated, the Six Sigma management paradox is as follows: To attain Six Sigma performance, we must minimize process variability, slack and redundancy by building variability, slack and redundancy...
Read more