All measurements involves uncertainty. Suppliers of measuring equipment usually specify the measurement uncertainty as a symmetrical interval around the measurement result:
Measurement result ± measurement uncertainty
Example: The length of a special measuring rod is 2000 mm ± 1 mm. With a 95 % confidence interval, which is normal to use, there is a 95% probability that the rod is between 1999 mm and 2001 mm.
Within Six Sigma, measurement system analysis (MSA), also referred to as measurement system evaluation (MSE), can determine the measurements accuracy, precision and stability. This is done by measuring the same item repeatedly and note the results. Based on the repeated measurements, the accuracy, precision and stability can be determined.
One of the tools in Six Sigma is CoV (Components of variation). A CoV can determine how much variation different factors causes. If you have a measurement, which is performed at different batches, by different analyst and by different monitoring equipment, a CoV can calculate how much each of these factors contribute to the overall measurement error. This is important to know if you are making decisions based on measurements that are affected by several factors.
Measurements are done in many different ways and with different kind of technologies within manufacturing companies. I have done measurement system evaluations of subjective measurements such as appearance, taste and smell. To my surprise, the measurement error for a visual test was greatest for the quality manager, who made the decision when there was doubt about the quality. The quality manager did not perform the test frequently, only occasionally when the quality was questioned. Ironically, this person evaluation involved more error than for operators whom performed the test more frequently.
Many companies use cameras / automatic optical inspection (AOI) to control product quality. The measurement can be performed based on reference points that the camera identifies. Measures of distance can be made between reference points in order to control product quality. Measurement System Evaluations that I have performed for camera controls show that they are both accurate and precise if they find the right reference point. Unfortunately, I experienced for many cases that they were unstable because they often failed to find the correct reference point and thus rendered incorrect measurement.
I recommend businesses to evaluate their measurements, especially measurements used for important decisions regarding quality. Here is a video about measurement error for a measurement you probably can relate to: my bathroom scale.