Life is full of uncertainty. In our daily lives, we recognize that anything we try to achieve or objective we try to meet will have an uncertain outcome and rarely will anything go according to plan. Einstein theorized that there is no uncertainty in nature, maintaining that the uncertainty only exists in our knowledge of it. Many scientists and physicists may disagree with Einstein in this regard, but wherever one might land on the subject, it is well established that the uncertainty of things weighs heavily in our lives.

In measurement, as in life, uncertainty has an important economic consequence for calibration and measurement activities. Measurement Uncertainty (not to be confused with measurement error) is a condition where a lack of information leads to an inadequate or incomplete measured result. Put in everyday terms, no one can state with any certainty that their expensive quartz watch is maintaining UTC time at 100% accuracy, but they can state that it is 99.9998% accurate “plus or minus” 0.1 seconds per day or that a measuring stick may be a meter in length “give or take” a centimeter. Every measurement, no matter how precise, always has a margin of doubt. Therefore, all measurements are subject to uncertainty, and by international consensus, a measurement result is only complete when it is accompanied by a statement of associated uncertainty.

In quality assurance, we rely heavily on measurement and we must consider that there are numerous contributors to uncertainty in all of our measurement systems. In a typical manufacturing environment, there are thousands of precision measurement devices, hundreds of operators using them, harsh environmental conditions, random processing events, even insufficient training or management contributing uncertainty to the measurement system as a whole. It is for this reason that companies rely on their calibration efforts to help maintain measurement and test equipment (M&TE), if not the entire measurement system. To perform these calibration functions without compromise, it is crucial that quality professionals choose and utilize effective calibration management software not only to track and maintain M&TE, but to effectively and completely estimate the uncertainty contributors in the measurement system.

Increasingly, more industries are beginning to wake up to the importance of tracking uncertainty contributions in their measurement activities. Some of the more stringent sectors, such as automotive, aerospace or medical device, will not choose a supplier that does not have systems in place to identify and document the associated uncertainty in their measurements. A comprehensive software package will provide a statistical analysis suite that includes the ability to establish Uncertainty Budgets from studies. These budgets allow the calibration technician to factor in multiple contributors to measurement uncertainty and to estimate the potential variability in gage, operator and product error. A typical budget will contain the M&TE’s stated or estimated uncertainty, factor in common operator error such as repeatability and parallax or even significant environmental conditions. The Uncertainty Budget (as outlined by A2LA or the ISO GUM) is the most comprehensive and effective tool we can employ to estimate uncertainty in our measurement activities.

In the end, we all must deal with the uncertainty in our lives, but with so many tools available to us, there is no reason to suffer uncertainty in our work. After all, the safety and quality of our products depend on it.

 

About the Author
Devin Brent Ellis is Director of Development and Client Solutions at CyberMetrics Corporation, developer and worldwide distributor of GAGEtrak calibration management and FaciliWorks CMMS maintenance management software.

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