Conformity assessment refers to activities undertaken to check whether some product, service or process meets certain criteria and specifications given by internationally accepted standards. The decision on whether a property of interest is aligned with the set standards is made based on measurement. However, uncertainty associated with the measurement results may lead to incorrect decisions. Measurement results may be falsely rejected as non-conforming, although they meet specifications. This is referred to as the producer’s risk. If the measurement result that does not meet the required specifications is accepted as conforming, this is referred to as the consumer’s risk. This paper covers calculations of global consumer's and producer's risk using the Bayesian approach and deals with the application of metrics related to confusion matrices in conformity assessments. These techniques have been used to assess the conformity of the bearing ring diameter with the given specifications. Based on the behavior of these metrics, the optimal length of the guard band was determined with the aim of minimizing the global consumer’s and producer’s risk.

The conformity assessment of products or a measured value with the given standards is carried out based on the global risk of producers and consumers’ calculations. A product may conform to specifications but be falsely rejected as non-conforming. This is about the producer’s risk. If a product does not meet the requirements but is falsely accepted as conforming, that poses a risk to the consumer. The conventional approach to risk assessment, which yields only a single numerical value for the global risk of producers and consumers, is naturally extended and utilized for assessing risk in measurement models with linear regression. The outcomes of the two-dimensional extension, along a moderate scale, are the parabolas with upwards openings. Risk surfaces were obtained through three-dimensional extension over the area limited by the moderate scale and guard band axes. Four models with different ranges of tolerance intervals were used to test this innovative method of risk assessment in linear regression. The corresponding standard measurement uncertainties were determined by applying a simplified measurement model with the use of comprehensive data on the measurement performance and by determining measurement uncertainty derived from consideration of the functional relationship obtained by linear regression analysis. Models that utilize information from linear regression analysis to determine measurement uncertainty are biased towards risks at the edges of the moderate scale. Testing the model’s performances with metrics related to the confusion matrix, such as the F1 score, further substantiated this assertion. The diagnostic odds ratio has been proven to be extremely effective in identifying the curve along the guard band axis, along which the global risks of producers and consumers are at their lowest.

This paper presents the conformity assessment process of the epoxy coating thickness applied on water pipes made of gray cast iron with the specifications given for this kind of coating appliance. An epoxy coating was applied to prevent a special form of corrosion called the graphitization of cast iron. In order for the pipe to withstand its designed service life, it is necessary to ensure the required thickness of the applied coating. In accordance with the EN 877 norm, the thickness of the epoxy coating on the pipes for the projected corrosiveness of the environment C4 and the durability of 20 years is at least 70 μm and this indicates the required accuracy of the product. To achieve the desired product quality, statistical control of the coating application process was carried out and the impact of uncertainty associated with the measurement result was analyzed. Considering the quality of the coating application process and the quality of the measuring system, and to ensure the quality of products and to reduce consumer risk, the optimal thickness of the coating was determined.

The conformity assessment of products or a measured value with the given standards is carried out based on the global risk of producers and consumers calculation. A product may conform to specifications but be falsely rejected as non-conforming. This is about the producer's risk. If a product doesn't meet the requirements but is falsely accepted as conforming, that poses a risk to the consumer. The conventional approach to risk assessment, which yields only a single numerical value for the global risk of producers and consumers, is naturally extended, and utilized for assessing risk in measurement models with linear regression. The outcomes of the two-dimensional extension, along a moderate scale, are the parabolas with an opening upwards. Risk surfaces were obtained through three-dimensional extension over the area limited by the moderate scale and guard band axes. Four models with different ranges of tolerance intervals were used to test this innovative method of risk assessment in linear regression. The corresponding standard measurement uncertainties are determined by applying a simplified measurement model with the use of comprehensive data on the measurement performance and by determining measurement uncertainty derived from consideration of the functional relationship obtained by linear regression analysis. Models that utilize information from linear regression analysis to determine measurement uncertainty are biased towards risks at the edges of the moderate scale. Testing the model's performances with metrics related to the confusion matrix, such as the F1 score, further substantiated this assertion. The diagnostic odds ratio has been proven to be extremely effective in identifying the curve along the guard band axis, along which the global risks of producers and consumers are at their lowest.

In the product quality assessment process, it is determined whether the product meets the specified requirements. The assessment is based on measuring the specific characteristics of the product. Depending on the measurement uncertainty, the risk of accepting a product that does not meet specifications can be assessed, i.e., the consumer's risk. Conversely, rejecting a product that meets specifications poses a risk for the manufacturer. The standard method of risk assessment by points has been expanded planar and spatially and was applied for risk calculation during the calibration of the roundness measurement device on a moderate scale from −3 µm to 3 µm. A known observation of the dependent variables is used to calculate the producer's and consumer's risk of the corresponding explanatory variable. The risk of calibration was performed for the linearized tolerance interval. Measurement uncertainty of the calibrated value was determined from the regression line by utilizing the propagation of error.