Repeatability conditions

Repeatability. This refers to two aspects of inspection similarity between objects that are inspected and possibility of maintaining constant inspection conditions (settings) for all the inspections performed. Obviously, interpretation of data in repeatable conditions is significantly simplified. Usually, inspection during or after manufacturing process will be repeatable. Another example of repeatable inspection is inspection of heat exchangers in power nuclear plants, inspection of aircrafts as these are well standardised. However, a large part of the NDT inspection done is not repeatable. 

Neural network classifiers. The neural network or other statistical classifiers impose strong requirements on the data and the inspection, however, when these are fulfilled then good fully automatic classification systems can be developed within a short period of time. This is for example the case if the inspection is a part of a manufacturing process, where the inspected pieces and the possible defect mechanisms are well known and the whole NDT inspection is done in repeatable conditions. In such cases it is possible to collect (or manufacture) as set of defect pieces, which can be used to obtain a training set. There are some commercially available tools (like ICEPAK [Chan, et al., 1988]) which can construct classifiers without any a-priori information, based only on the training sets of data. One has, however, always to remember about the limitations of this technique, otherwise serious misclassifications may go unnoticed. 

Analyze the 2n test portion (12p) in random order imder repeatable conditions (two wells). 

In spite of all these efforts, the final responsibility for any analytical results obtained by European Standard methods remains with the analyst who obtained the result. To underline this responsibility, the obligation is included in each standard that each laboratory should periodically determine if its results under repeatability conditions are acceptable... . 

Repeated measurements of the same measurand on a series of identical measuring samples result in random variations (random errors), even under carefully controlled constant experimental conditions. These should include the same operator, same apparatus, same laboratory, and short interval of the time between measurements. Conditions such as these are called repeatability conditions (Prichard et al. [2001]). The random variations are caused by measurement-related technical facts (e.g., noise of radiation and voltage sources), sample properties (e.g., inhomogeneities), as well as chemical or physical procedure-specific effects. 

Repeatability is the closeness of the agreement between the results of successive measurements of the same measurand carried out under the same conditions of measurement . Repeatability conditions include the same measurement procedure, the same observer, the same measuring instrument, used under the same conditions, the same location, and repetition over a short period of time (ISO 3534-1 [1993]). 

Experimental standard deviation obtained from a series of n measurements under repeatability conditions. 

A confidence interval representing the maximum permitted difference between two single test results under repeatability conditions ... 

The measurement bias, B, can be calculated as the ratio (often expressed as a percentage) of the difference between the mean of a number of determinations of a test sample, obtained under repeatability conditions, and the true or accepted concentration for that test sample, as shown in the following equation ... 

Repeatability Precision under repeatability conditions, i.e. conditions where independent test results are obtained with the same method on identical test items in the same laboratory by the same operator using the same equipment within short intervals of time. 

Repeatability limit The value less than or equal to which the absolute difference between two test results obtained under repeatability conditions may be expected to be with a probability of 95%. 

A run is therefore regarded as being carried out under repeatability conditions, i.e. the random measurement errors are of a magnitude that would be encountered in a short period of time. In practice the analysis of a run may occupy sufficient time for small systematic changes to occur. For example, reagents may degrade, instruments may drift, minor adjustments to instrumental settings may be called for, or the laboratory temperature may rise. However, these systematic effects are, for the purposes of IQC, subsumed into the... 

The error estimate based on replicates at nominal level results in underestimated critical effects, and consequently a high number of effects is considered significant, which practically are not relevant, e.g., the effects of A, C, D, I, E, and J on response Rs at significance level a = 0.05 (Table 10). A possible reason is that the replicates are measured under repeatability conditions. For duplicated design experiments, a similar problem might occur. However, in Table 11 it is not the case or the critical effect is only slightly underestimated. In case underestimation occurs for a response related to the quantitative aspect, the method would incorrectly be considered non-robust, since effects considered significant occur. This is fundamentally not a problem, because one will react when it is not necessary. It just leads to a waste of time and money. The opposite situation is worse. 

It is an indicative valne and should not normally be nsed for decision-making pnrposes. It shonld be established nsing an appropriate measurement standard or sample and should not be determined by extrapolation. The LoQ is calculated as the analyte concentration corresponding to the sample blank value plus 10 standard deviations of the blank measurement. If measurements are made under repeatability conditions, a measure of the repeatability precision at this concentration is also obtained. 

The intermediate precision is what we encounter in the everyday laboratory practice. A laboratory can, for example, calculate the precision tmder repeatability conditions (same day, same method, same operator etc., but using different equipment, or same equipment but different operators etc.). 

Repeatability conditions and reproducibility conditions are extreme cases... 

There are different standard deviations depending on the measurements conditions repeatability conditions, between-batch and interlaboratory reproducibility conditions. 

CRMs would be the ideal control samples, but they normally are too expensive and very often not available. In-house reference materials that are regularly checked against a CRM under repeatability conditions are a good alternative. 

One of the aims of a validation study is to establish the repeatability and reproducibility precision. Experiments performed under repeatability conditions (see chapter 2) are those repeated over a short period of time, with the same analyst and same equipment. For an analysis, the repeats must be independent, involving the entire method, and not simply the operation of the instrument several times. Reproducibility conditions are the sine qua non of the interlaboratory study. Different laboratories, with different analysts, instruments, reagents, and so on, analyze the sample at different times, but all with the same method. The relationship among these parameters is shown in figure 5.5. 

Comparability is a key property of chemical measurements. While results can be compared directly under repeatability conditions, a more general approach is needed to provide meaningful comparison to results of other measurements made at different times and places. This comparability over space-and-time is routinely achieved by linking the individual measurement results to some common, stable reference or measurement standard. Results are therefore correlated to that reference. This strategy of linking results to a reference is termed traceability [1,2], Traceability is a key property in metrology, and for this reason the traceability of results is even explicitly demanded in the international norm ISO 17025 [3]. 

If the test result as an average of several individual measurements is obtained with the same method from an identical test sample, in the same laboratory, by the same analyst, with the same instrumentation, over a short period of time, then the study takes place under repeatability conditions. On the other hand, reproducibility conditions occur when the measurements take place following the same procedure and using identical samples but in different laboratories using different analysts with different instrumentation. 

One laboratory has carried n measurements under repeatability conditions and obtained an average value y which is compared with a given value m0 (e.g. a specific migration limit). Then one obtains the critical difference as ... 

Within laboratory (repeatability conditions) precision according to ISO 5725... 

Random error — The difference between an observed value and the mean that would result from an infinite number of measurements of the same sample carried out under repeatability conditions. It is also named indeterminate error and reflects the - precision of the measurement [i]. It causes data to be scattered according to a certain probability distribution that can be symmetric or skewed around the mean value or the median of a measurement. Some of the several probability distributions are the normal (or Gaussian) distribution, logarithmic normal distribution, Cauchy (or Lorentz) distribution, and Voigt distribution. Voigt distribution is... 

Median — The middle value of a set of data sampled under repeatability conditions, and that has been arranged in order of size. For an even number of observations, the mean of the middle pair is used [i]. 

Mean — The average value computed from a set of data sampled under repeatability conditions. When the number of observations approaches to infinity, the mean of such a huge set of data is called -> population mean (ft),... 

Since the state of a system is a unique and repeatable condition, we wish to express all results in terms of state variables or changes in state variables. So far we have introduced three state valuables, U, S,... 

The analyst performs 10 measurements under repeatability conditions and has determined the repeatability standard deviation to be 0.12. 

Repeatability, measurement precision under a set of repeatable conditions of measurement [3] precision of results obtained under the same measurement conditions (a given laboratory, analyst, measuring instrument, reagents, etc.). 

The repeat standard deviation describes the scattering of the measuring results under repeat conditions (same laboratory, same equipment, same staff). Whereas, the between laboratory standard deviation expresses the differences between the laboratories. The reproduce standard deviation contains the two above mentioned scatter components. It is the deviation under reproduce conditions (different laboratories, different equipment, different staff). To get a unique repeat standard deviation it must be assumed that it does not vary (significantly) with the laboratory. For this reason the standard recommends a statistical outlier test (Cochran test) for the individual standard deviations of the laboratories. Furthermore, the individual laboratory means are a subject to an outlier test (Grubbs test). 

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