Measurement Uncertainty:
What Utility Engineers Need to Know

The importance of measuring uncertainty in engineering cannot be overstated. This article aims to clarify the concept for utility engineers, emphasizing its implications. In the realm of measurements, accuracy is key. It's important to acknowledge that no measurement is flawless. There will always be a margin of error.

To tackle this issue, the Guide to the Expression of Uncertainty in Measurement (GUM) was created by the Joint Committee for Guides in Metrology (JCGM). This guide lays out a method for quantifying and communicating uncertainty in testing and calibration procedures.

Ensuring Accuracy - An engineer checks parameters with an oscilloscope, illustrating the importance of understanding and applying measurement uncertainty principles
Ensuring Accuracy: An engineer checks parameters with an oscilloscope, illustrating the importance of understanding and applying measurement uncertainty principles

The GUM outlines a process for assessing uncertainty through identification, modelling and calculation. It defines uncertainty as a parameter that represents the range of values to the measured quantity.

For example, consider an engineer measuring voltage across a resistor, with a multimeter. After taking readings under conditions, they determine that the average voltage is 10.5 volts.
This is the estimation of the actual voltage reading.

Now following the guidelines of the GUM the engineer must also take into consideration the uncertainty linked to this measurement. They factor, in elements like the precision of the multimeter the stability of the measurement setup and the accuracy of the calibration standards employed.

After analysing repeated measurements, the engineer establishes that the Type A uncertainty for this voltage reading is approximately ±0.2 volts. Furthermore, they refer to the manufacturers specifications. Confirm that the Type B uncertainty is around ±0.3 volts.

To compute the combined uncertainty, statistical laws of propagation are used by combining both Type A and Type B uncertainties. In this scenario, it results in a combined uncertainty of √(0.2² + 0.3²) = ±0.36 volts.

Each input quantity influencing the measurement undergoes an evaluation for both types of uncertainties. By modelling their interrelations and determining sensitivities, these uncertainties are integrated using principles to calculate a standard uncertainty. This value is then represented as an expanded uncertainty, offering an estimated range to contain the value of what was measured.

Following GUM ensures result traceability, consistency, in assessing uncertainties and informed utilization of measurement data.
The GUM framework is widely. Utilized across sectors such, as mechanical engineering, chemistry, healthcare and more. By following the guidelines set forth in the GUM engineers can confidently communicate measurement uncertainty, thereby upholding the trustworthiness and dependability of their test outcomes.


It is crucial for utility engineers to grasp and implement the fundamentals of uncertainty to ensure dependable results. Through compliance with the GUM framework, engineers can bolster the trustworthiness and validity of their measurements, ultimately leading to decision-making processes and operational effectiveness.

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