Wouldn’t it be nice to catch quality or safety issues before they generate defects, incidents, injuries? Using Statistical Process Control (SPC), this can be a reality.
By Nicole Radziwill
Although random variation in a process is to be expected, “special causes” for variation -- like a machine that needs to be recalibrated, or an operator who needs additional training -- should be addressed as soon as possible. SPC is a mathematical method dating back to the 1920’s that provides an “early warning system” when a process starts to drift away from its performance targets.
But an early warning will only be beneficial if you can act on the signal it provides -- and follow through with actions to restore the system to order. Managing the response to a quality event like an early warning is something that Intelex systems do well.
The mathematical method used in SPC is based on the probability that a random process will behave a certain way. For example, think about flipping a coin. There’s a 50% (0.5) chance that the coin will come up heads, and a 50% chance it will come up tails (if it’s a fair coin). To determine the probability that the coin will come up heads twice in a row, we use the multiplication rule: 0.5 x 0.5 = 0.25, or a 25% chance. Using the same approach, the chance that the coin will come up heads three times in a row is 0.5 x 0.5 x 0.5 = 0.125 (12.5%), four times in a row is 6.25%, and five times in a row is just over 3%.
Getting five or more heads in a row is pretty uncommon -- and will only occur by chance 3 or fewer times out of every 100 opportunities, if the coin-flipping process is truly random. As a result, one of the common “run rules” is to declare a process “out of control” when there is a trend of 6 points in a row increasing or decreasing. Although there are additional run rules that can be applied, they were all devised using a similar probabilistic argument.
In December 2018, Intelex partnered with InfinityQS, a leader in data-driven manufacturing quality, to unite the early warning system of SPC with the Intelex management system -- that helps you keep track of the activities that need to be coordinated when special cause variation is observed.
SPC is a true EHSQ tool, because it can also be used illuminate health and safety issues before they lead to noncompliance or disaster. For example, you can track time series of environmental variables like emissions, or metrics like days since last incident or days since a “never event” (in healthcare). If the variable you’re measuring is showing patterns that can not be attributed to random, expected variation, the early alert can accelerate your response.
Gaddis, S. (2018). Unleash a Better Safety Culture by Controlling Process Variability. Intelex Insight Report. Available from https://www.intelex.com/resources/insight-report/unleash-better-safety-c...
Intelex. (2018, Dec 4). Intelex partners with Quality & SPC Leader InfinityQS to deliver the most comprehensive cloud Quality Management System. https://www.intelex.com/about/press-room/intelex-partners-quality-spc-le...
McLean, D. (2018, July 19). Tightening Processes is Key to Worker Safety. Available from https://blog.intelex.com/2018/07/19/unleash-better-safety-culture-contro...
About the Author: Nicole Radziwill Quality Practice Lead
Nicole Radziwill is the Quality Practice Lead at Intelex Technologies. Before Intelex, she was an Associate Professor of Data Science and Production Systems, Assistant Director (VP) End-to-End Operations at the National Radio Astronomy Observatory (NRAO), and manager and consultant for several other organizations since the late 1990's bringing quality management to technologically-oriented operations. She is a Fellow of the American Society for Quality (ASQ) with a Ph.D. in Quality Systems from Indiana State University. Nicole serves as Editor of Software Quality Professional (SQP) journal and is a former Chair of the ASQ Software Division. She is an ASQ Certified Manager of Quality and Organizational Excellence (CMQ/OE) and Certified Six Sigma Black Belt (CSSBB).
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