Determining measurement uncertainty
07 July 2015
Evelyne Lösch, technical trainer at HBM, explains the GUM-based approach for evaluating measurement uncertainty and explains the advantages of adopting a common approach.
When we talk about ‘uncertainty’ in everyday use, it doesn’t really inspire much confidence. However when used in a technical sense, as in ‘measurement uncertainty’ or ‘uncertainty of a test result’, the term actually refers to the quality of a measurement and focuses on the doubt that exists about the result.
The fundamental issue is that all measurements have an associated uncertainty, and if the uncertainty is not understood, the result of a measurement may lead to incorrect conclusions. Most measurements are subject to some form of imperfections; some of these may be due to random effects, such as short-term fluctuations in temperature, humidity and air pressure or variability in the performance of the tester, while other imperfections could be due to the practical limits within the test. These limits could include the offset of a measuring instrument, a drift in characteristics between calibrations, personal bias in reading an analogue scale or the uncertainty of the value of a reference. So, how do we determine an accurate result of a measurement?
Certainty versus uncertainty
Error and error analysis have long been part of the practise of measurement science. It is now widely recognised that, when all of the known or suspected components or error have been evaluated and the appropriate corrections have been applied, there still remains an uncertainty regarding the accuracy of the stated result. For example, a doubt about how well the result of the measurement represents the value of the quantity being measured.
With this in mind, we can see why it is necessary that a readily implemented, easily understood and, generally accepted procedure for characterising the quality of a result of a measurement is necessary for evaluating and expressing its uncertainty. This is where The Evaluation of Measurement Data – Guide to the Expression of Uncertainty in Measurement (GUM) fits in.
One size fits all
First published in 1993 and revised in 2008 by the International Organisation for Standardisation (ISO), the GUM provides a unified approach for the determination and expression of measurement uncertainty.
Just as the universal use of the International System of Units (SI) has brought coherence to all scientific and technological measurements, the GUM-based approach offers a global consensus of the evaluation and expression of uncertainty in measurement and permits the significance of a vast spectrum of measurement results across a variety of fields - including engineering - to be easily understood and properly interpreted worldwide.
Generally speaking, the focus of the GUM is to establish general rules for evaluating and expressing uncertainty in measurement that can be followed at various levels of accuracy and across many fields. As a consequence, the principles of the approach are intended to be applicable to a broad spectrum of measurements including those required for:
- Maintaining quality control and quality assurance in production.
- Complying with enforcing laws and regulations.
- Conducting basic research, and applied research and developments, in science and engineering.
According to the GUM-based approach, uncertainties are split into two categories; Type A and Type B. Type A focuses on the evaluations of uncertainty based on the statistical analysis of a series of measurements while Type B concentrates on the evaluations of uncertainty, which are based on other sources of information, such as an instrument manufacturer’s specification, a calibration certificate or values published in a data book.
The main advantages of applying the GUM-based approach is the fact that it is an internationally accepted approach to calculating and expressing uncertainties, which allows everyone to ‘sing from the same song sheet. However, it has also received criticism.
It has been suggested that, despite affirmation that the approach will be applied long term, there is comparatively little material available to assist in the teaching of this topic. However, to circumvent this, a variety of training courses have now become available to offer delegates the opportunity to learn and practise the GUM-based approach.
The HBM Academy Uncertainty Measurement training course, for example, aims to provide an appreciation of the concept of uncertainty of measurement in a calibration or testing environment. To ensure international acceptance, this course is based on the ISO GUM Method and is designed to directly address the ISO/IEC17025 measurement uncertainty analysis requirements in a practical, compliant and efficient manner.
Aimed at all measurement engineers in charge of planning and taking measurements, as well as users performing measurement data tasks. Every effort is made to eliminate unnecessary complications and to apply The Guide to the Expression of Uncertainty in Measurement (GUM) at its simplest level and remove any mystery associated with measurement uncertainty.
Through a combination of interactive tutorials and lectures, the HBM course guides delegates through the process of calculating uncertainties and explains ways of estimating the Measurement Uncertainty according to the GUM guideline, without high mathematics.
Robert Leese, test engineer at Perkins Engines attended the course. He said: “My colleague and I really enjoyed the course and both gained a lot, it was very informative and the resources were very good.”
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