New Publication: The Importance of a Proper SPC Subgroup Sampling Technique

                A common error of many six sigma and operations research professionals is not properly selecting the correct subgroup sampling technique when constructing a Statistical Process Control (SPC) chart. Incorrect subgroup sampling technique selection has become worse in the modern computing age – perhaps because most practitioners try to “fit” their data into the GUI template of the major statistical software packages. Consequently, many practitioners produce aesthetically appealing charts that are simply not effective at identifying out-of-control (OOC) conditions. This paper will discuss proper SPC subgroup sampling techniques and illustrate the principles of proper subgroup sampling selection from a practitioner’s perspective.

This article first appeared in Quality Digest (www.qualitydigest.com ) and can be viewed at: 

http://www.qualitydigest.com/inside/quality-insider-article/importance-proper-spc-subgroup-sampling-technique.html

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Author: John Kendrick

John David Kendrick is a certified Six Sigma Master Black Belt and a principal with Business Process Management Inc. His professional interests include quality, private equity, and quantitative finance. He holds a master of engineering degree in simulation and modeling from Arizona State University; master of applied statistics from Penn State, and a master of business administration in finance from the University of Pittsburgh. His undergraduate degrees are a bachelor of science in physics from Purdue; a bachelor of science in math/computer science from the University of Pittsburgh; and a bachelor of arts in economics from the University of Pittsburgh. He is a senior member of the American Society of Quality (ASQ) and is ASQ-certified as: CSSBB, CRE, CSQE, CQM/OE. He also holds two lean certifications.