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American Society for Quality The Importance of Understanding Type I and Type II Error in Statistical Process Control Charts Presented by: Dr. Phil Rosenkrantz Statistical methods that involve sampling of any kind are subject to two kinds of sampling error: Type I error is when your sample or test leads you to conclude a process is bad but it is really acceptable (a.k.a “producer’s risk” or a “false alarm”). Type II error is when your sample or test leads you to conclude that a process is operating OK but it is really not (a.k.a “consumer’s risk” or “failure to detect”). Wrong conclusions lead to incorrect actions. In the world of quality the bigger concern is almost always Type II error such as thinking a part, batch or process is good when it is really not. However, a major exception to this thinking is found in the use of statistical process control (SPC) charts where Type I error (false alarms) can cause people to hunt for problems that don’t exist which destroys user confidence and damages the implementation of SPC very quickly. In my consulting experience this is a common problem that is largely misunderstood. The major culprits are usually the decision rules being used to alert that the process is out-of-control. The focus of this presentation is Type I error. The goals of this presentation are to: Provide a brief review of the concepts of process control and process capability Explain Type I and Type II error with colorful examples Give examples of Type I and Type II error for common decision rules Illustrate how the improper use of decision rules creates excessive Type I error and creates mistrust in the use of SPC Suggest simple approaches for reducing Type I error in SPC Background Dr. Phil Rosenkrantz is Professor Emeritus of Industrial & Manufacturing Engineering at Cal Poly Pomona where he has been teaching and consulting for 34 years and served as Department Chair from 1990-1997. He was also founding Coordinator of the MSQA Program at CSU Dominguez Hills from 1986-1989. Phil was an engineering supervisor for General Motors prior to entering academia. Educational background includes Doctor of Education in Organizational Leadership from Pepperdine University; MS in Statistics from UC Riverside; MS in Industrial Administration from Purdue University; and B.S. in Mechanical Engineering from Kettering University (formerly GMI). P.E. (California). 2005 Recipient of the Simon Collier Award. George P. Hart Award for Outstanding Faculty Leadership 1999. Outstanding Teacher Award for the College of Engineering 2012. Phil has been active in ASQ and ASEE (American Society for Engineering Education). Over the years Phil has been a volunteer with the Boy Scouts of America (8 years), the Board of Directors of Eastside Christian Schools (27 years), and U.S. Forest Service (20 years).