John Flaig

Managing director

John J. Flaig, Ph.D., is a fellow of the American Society for Quality and is managing director of Applied Technology at www.e-at-usa.com, a training and consulting company. Flaig has given lectures and seminars in Europe, Asia, and throughout the United States. His special interests are in statistical process control, process capability analysis, supplier management, design of experiments, and process optimization. He was formerly a member of the Editorial Board of Quality Engineering, a journal of the ASQ, and associate editor of Quality Technology and Quantitative Management, a journal of the International Chinese Association of Quantitative Management.

Thu, 05/12/2011 - 06:00
A Bell-Shaped Distribution Does Not Imply Only Common Cause Variation Random does not imply normal
Mon, 09/18/2017 - 12:03
Story update 9/26/2017: The words "distribution of" were inadvertently left out of the last sentence of the second paragraph. Some practitioners think that if data from a process have a “bell-shaped” histogram, then the system is experiencing only…
Auditors Must Be IndependentIf an auditor is hired by the company it’s supposed to audit, is it truly independent?
Mon, 08/21/2017 - 12:03
Independence is an important issue in statistics, so I found the article, “Ethics, Auditing and Enron,” by Denis Arter and J. P. Russell, in the October 2003 issue of Quality Progress quite interesting. In the second section of the article the QP…
Process Capability Confusion Caused by Skewed DistributionsDoing the math right but getting the answer wrong
Wed, 05/31/2017 - 12:03
In a similar vein to Donald Wheeler’s excellent article on process capability confusion I would like to submit the following example of thinking that you are doing the math right and getting an answer that can get you into real trouble. Consider…
The Short-Term and Long-Term Confusion‘Everything should be made as simple as possible, but not simpler’
Mon, 03/21/2016 - 17:25
Sometimes when authors try to make a technical concept more understandable, it’s simplified but unfortunately, less accurate. For example, when the developers of Six Sigma wanted to explain control charts and process capability analysis, they…
The Economics of Project ManagementTo know how a project will affect revenues, first understand how it relates to other projects
Wed, 08/05/2015 - 16:38
I have discussed the economics of project management numerous times in presentations all over the country, and based on the response to my message, I have to conclude that many people just don’t get it. Let me again sound the wake-up call with a…
Rethinking Failure Mode and Effects AnalysisA better method takes into account economic loss
Wed, 06/24/2015 - 14:54
The classic version of FMEA is an engineering tool for quality and reliability improvement through project prioritization. It was formally released by the U.S. government with MIL-P-1629 in 1949 and updated in 1980 as MIL-STD-1629A. The classic…
Is the 1.5 Sigma Shift an ‘Ill-Conceived Safety Margin?’The hidden use of safety margins in quality engineering
Mon, 02/24/2014 - 15:02
Engineers have used safety margins for centuries to protect their companies and customers from the consequences of product degradation and failure. Sometimes the safety margins are fairly obvious (e.g., maximum-load limits posted in elevators), and…
Does C = 0 Sampling Really Save Money?Only if you count just the cost of the customer’s inspection
Mon, 08/05/2013 - 16:32
The claim is made and widely believed that C = 0 sampling plans are more cost effective than classic sampling plans such as ANSI/ASQ Z1.4. Below is a preliminary analysis of the cost difference between the two sampling plans using the…
The Risks in Root Cause AnalysisA good design of experiments can prevent incorrect conclusions
Thu, 04/04/2013 - 13:14
What’s wrong with root cause analysis? Let’s begin with the name, which is singular. It implies that there is only one root cause, when in reality most problems are usually caused by a complex combination of several factors, some of which are more…
Rethinking the 80–20 RuleThere’s a better approach for prioritizing projects
Wed, 03/06/2013 - 10:32
Everyone in the quality world is familiar with the famous 80–20 rule for corrective action project prioritization. The “rule” suggests that 20 percent of the causes result in 80 percent of the effects or in technical terms, the principal of factor…