If you don’t know the measurement uncertainty, don’t make the measurement at all!
This time we are talking about one very fundamental consideration in any measurement or calibration – uncertainty!
I recently made a new white paper on calibration uncertainty, please take a look at it. This paper discusses the basics of uncertainty in measurement and calibration. It is designed for people who are not mathematicians or metrology experts, but rather for people who are planning and making the practical measurements and calibrations in industrial applications.
You can download the free white paper as a pdf file, by clicking the below picture:
Being aware of the uncertainty related to the measurement is a very fundamental concept and you should not really make any measurements unless you are aware of the related uncertainty.
It seems that the generic awareness of and interest in uncertainty is growing, which is great.
The uncertainty of measurements can come from various sources such as: the reference measurement device used to make the measurement, environmental conditions, the operator making the measurements, the procedure, and many other sources.
There are several calibration uncertainty guides, standards, and resources available out there, but these are mostly just full of mathematical formulas. In this paper, I have tried to keep the mathematic formulas to a minimum.
The uncertainty estimation and calculation are pretty complicated, but I have tried my best to make some common sense out of it.
What is the uncertainty of measurement? Shortly and simply we can say that it is the “doubt” of the measurement, so it tells us how good the measurement is. Every measurement we make has some “doubt” and we should know how much this “doubt” is, to decide if the measurement is good enough for the usage.
It is good to remember that error is not the same as uncertainty. In calibration, when we compare our device to be calibrated against the reference standard, the error is the difference between these two readings. The error does not have meaning unless we know the uncertainty of the measurement.
Classic “piece of string” uncertainty example
Let’s take a simple example to illustrate the measurement uncertainty in practice; we give the same piece of a string to three different people (one at a time) and ask them to measure the length of that string. There are no additional instructions given. They can all use their own tools and methods to measure it.
More than likely, you will get three somewhat different answers, such as:
- The first person says it is about 60 cm. He used a ten cm plastic ruler and measured the string once and came to this conclusion.
- The second person says it is 70 cm. He used a three-meter measuring tape and checked the results a couple of times to make sure he was right.
- The third person says it is 67.5 cm, with an uncertainty of ±0.5 cm. He used an accurate measuring tape and measured the string multiple times to get an average and standard deviation. Then, he tested how much the string stretches when it is pulled and noticed that this has a small effect on the result.
Even this simple example shows that there are many things that affect the result of measurement: the measurement tools that were used, the method/process that was used, and the way that the person did the job.
So, the question you should be asking yourself is:
At your plant, when calibration work is performed, which of these three above examples will it be?
What kind of “rulers” are being used at your site and what are the measuring methods/processes?
If you just measure something without knowing the related uncertainty, the result is not worth much.
I hope you got something out of this first look into the exciting world of calibration uncertainty. To learn more about the subject, please take a look at the white paper. Here is a short list of the key takeaways from the white paper:
- Be sure to distinguish “error” and “uncertainty”
- Experiment by repeating your measurements to gain knowledge of the typical deviation
- Use appropriate reference standards (calibrators) and make sure they have valid traceability to national standards and that the uncertainty of the calibration is known and suitable for your applications
- Consider if the effect of the environmental conditions are significantly affecting the uncertainty of your measurements
- Be aware of the readability and display resolution of any indicating devices
- Study the specific important factors of the quantities you are calibrating
- Familiarize yourself with the “root sum of the squares” method to add independent uncertainties together
- Be aware of the coverage factor / confidence level / expanded uncertainty, of the uncertainty components
- Strive to be more aware of all the related uncertainties, not just the TAR/TUR ratio.
- Pay attention to the total uncertainty of the calibration process before making pass/fail decisions
I will make additional posts continuing on the uncertainty subject in the near future, stay tuned!
Part 2 & Part 3 of this article
This article continues in the below-linked posts:
You may also like this one related to uncertainty:
Also, please check out the article What is calibration on our website.