Measurement Uncertainty In Testing Research Articles

Measurement uncertainty in testing of biologicals in national control laboratories for ISO/IEC 17025: practical approaches

Measurement uncertainty in testing of biologicals in national control laboratories for ISO/IEC 17025: practical approaches

Standards and Assessment of Construction Products: Case Study of Ceramic Tile Adhesives

This work attempts to draw attention to the importance of a multidimensional approach when creating standard requirements in the assessment of construction products with the example of ceramic tile adhesives (CTAs). CTAs are an essential group of building materials today, the continuous development of which has been noted since the 1960s. However, until 2001, i.e., the year when EN 12004 was published, there were no precise requirements for CTAs at the European level, which often made it difficult or, in extreme cases, even impossible to assess the product objectively. Under the provisions of EN 12004, for twenty years, the basis for the assessment and verification of constancy of performance (AVCP) of CTAs has been adhesion determined by tensile strength. The paper discusses the test methods, paying attention to their imperfections, including the impact of the materials used in measurements, i.e., concrete slab, ceramic tile, and water quality. The results of the multi-annual interlaboratory tests indicate that an essential factor that must be considered in the process of AVCP is test measurement uncertainty. Additionally, it should be remembered that uncertainty also occurs at other assessment levels. It also seems that the simple acceptance rule that does not consider the variability resulting from the measurement uncertainty is inadequate when assessing CTAs.

Uncertainty of measurement and conformity assessment

Knowledge of the measurement uncertainty of test results is fundamentally important for laboratories, their customers and all parties using and interpreting these results. In conformity assessment, a measurement result is used to decide if an item of interest conforms to a specified requirement. Because of measurement uncertainty, there is always the risk of incorrectly deciding whether or not an item conforms to a specified requirement based on the measured value of a property of the item. Conformity assessment can be quite challenging when the entity measured is so close to the tolerance limits of the specification that its uncertainty, however estimated, critically affects decision-making. In such cases, different decision rules can be used to make statements of conformity. The aim of this paper is to provide a survey of methods for the evaluation of measurement uncertainty in testing, as well as to stress the need for appropriate estimation of measurement uncertainty. This paper also aims to assist testing laboratories in understanding the different decision rules used in conformity assessment and level of risk (such as false accept and false reject) associated with the decision rule employed.

Evaluating Risk in an Abnormal World: How Arbitrary Probability Distributions Affect False Accept and Reject Evaluation

Risk mitigation strategies commonly use the test uncertainty ratio (TUR) and end-of-period reliability (EOPR) to ensure a measurement is adequate for making acceptance decisions. Unfortunately, the common guidance of maintaining a TUR of at least 4:1 was developed to simplify the underlying calculus in an era predating modern computing and assumes that the probability distributions describing the product and the measurement uncertainty are unbiased and normally distributed. The Guide to the Expression of Uncertainty in Measurement and its supplements describe several situations where uncertainty in the measurement will not follow a normal distribution. Despite the evidence of non-normal behavior in measurements and products, risk evaluations typically assume normality in both distributions. While evaluating the probability of false accept (PFA) and the probability of false reject (PFR) is more challenging when the probability distributions are non-normal, the calculus is straightforward using either numerical integration or Monte Carlo techniques. This work considers several case studies of risk evaluation, including both global and specific risk, when the product or the test measurement uncertainty do not follow normal distributions. Neglecting non-normal behavior might greatly affect PFA and PFR by either over- or underestimating the probabilities depending on the parameters of the distributions.

Toward a Framework for Outcome-Based Analytical Performance Specifications: A Methodology Review of Indirect Methods for Evaluating the Impact of Measurement Uncertainty on Clinical Outcomes.

For medical tests that have a central role in clinical decision-making, current guidelines advocate outcome-based analytical performance specifications. Given that empirical (clinical trial-style) analyses are often impractical or unfeasible in this context, the ability to set such specifications is expected to rely on indirect studies to calculate the impact of test measurement uncertainty on downstream clinical, operational, and economic outcomes. Currently, however, a lack of awareness and guidance concerning available alternative indirect methods is limiting the production of outcome-based specifications. Therefore, our aim was to review available indirect methods and present an analytical framework to inform future outcome-based performance goals. A methodology review consisting of database searches and extensive citation tracking was conducted to identify studies using indirect methods to incorporate or evaluate the impact of test measurement uncertainty on downstream outcomes (including clinical accuracy, clinical utility, and/or costs). Eighty-two studies were identified, most of which evaluated the impact of imprecision and/or bias on clinical accuracy. A common analytical framework underpinning the various methods was identified, consisting of 3 key steps: (a) calculation of "true" test values; (b) calculation of measured test values (incorporating uncertainty); and (c) calculation of the impact of discrepancies between (a) and (b) on specified outcomes. A summary of the methods adopted is provided, and key considerations are discussed. Various approaches are available for conducting indirect assessments to inform outcome-based performance specifications. This study provides an overview of methods and key considerations to inform future studies and research in this area.

Measurement Uncertainty in Tests of Cast Irons

Focusing on heritage structures, various non-destructive tests (NDT) or minor-destructive techniques (MDT) can be applied while the application of destructive testing is limited. The probabilistic models for tensile and compressive strengths of historic cast iron are developed on the basis of destructive tests (DTs) and MDTs, respectively. NDT results are critically compared with DTs. It appears that numerous uncertainties affecting estimated resistance can be treated by statistical approaches along with the semi-probabilistic verification method. Non-destructive hardness tests can hardly be used to estimate strength of cast iron and must be supplemented by destructive tests.

Methods to assess the impact of test measurement uncertainty on downstream clinical outcomes: A case study of faecal calprotectin (FC) for the diagnosis of Inflammatory Bowel Disease (IBD)

The psychological research on the formation of collective memories has explored how individuals come to hold similar memories following conversational interactions in social networks. These collective memories are dependent on both individual-level cognitive mechanisms as well as on the social influence exerted during people's conversations. Building on this work, we investigate the impact of the network structure of conversational interactions on the formation of collective memories in 16-member networks. We manipulate two parameters of conversational networks that were previously found to impact information diffusion in networks: network reachability and network clustering. We find that clustering significantly impacts the emerging collective memory, but reachability does not. Additionally, a participant's influence on the content of the network's collective memory depends on both their topological position in the network and on how early their conversations occur in the conversational network.

Beyond the laboratory: A review of indirect methods to assess the impact of test measurement uncertainty on downstream clinical and cost outcomes

Beyond the laboratory: A review of indirect methods to assess the impact of test measurement uncertainty on downstream clinical and cost outcomes

Measurement Uncertainty in Testing of Uniaxial Compressive Strength and Deformability of Rock Samples

NE of the basic and most used methods of testing which is performed on rock samples is determination of uniaxial compressive strength and deformability. The testing method is proposed by the International Society for Rock Mechanics [1] in the form of Suggested Method and based on the guidelines in this document, some national standards were derived. Subsequently, additional documents [2] have been published that describe requirements and difficulties that arise from implementation of testing in detail and methods to overcome these difficulties. The latest literature dealing with determination of rock sample properties [3] has replaced [4] and [5]. Reference [3] is extended standard test method which also includes confined testing in various temperatures when compared to [2]. Similar testing is performed on other types of materials like concrete [6] and metals [7] - [9] with some differences in testing procedures and minimum measurement equipment properties. Testing of concrete sample properties has the most similarities with the testing of rock samples. The metals are tested for tensile strength as opposed to rock and concrete. Homogeneity of metallic materials is better than in concrete samples. Also, homogeneity of concrete samples is usually better than in rock samples. Homogeneity is important because it influences repeatability of measurement. According to the method [2], a rock sample of 54 mm in diameter and height from 2.5 to 3 times higher than its diameter is placed in the compression test machine and compressive force is applied to the sample. The force should have constant increase over time until the sample breaks and is disintegrated while simultaneously axial and lateral deformations are measured. The result is uniaxial compressive strength, i.e., stress at which the sample is disintegrated. If axial deformations are measured, Young’s modulus of elasticity can be obtained. If lateral deformations are measured, the sample’s Poisson’s coefficient is also obtained. A large difficulty in implementing the presented measurements is sample nonhomogeneity. Therefore, repeated measurements in equal conditions using different samples will give a variation in measurement results caused by material structure, i.e., nonuniform grain size, arrangement and micro cracks. It is not unusual that this variation is in the range of more than a few percent, i.e., 20 % [10]. Therefore, at least five samples are tested and the results are averaged to represent the properties of the material from which the samples are obtained. It is suggested that test results from samples which substantially deviate from the average are not used for calculating the final result. Rock samples can have uniaxial strength in the range from 5 MPa for soft rock, up to 250 MPa for very brittle rock. Concurrently, Young’s modulus of elasticity is in the range from 5 GPa to 120 GPa. Poisson’s ratio is mostly in the range from 0.1 to 0.45.

Measurement uncertainty in testing for antimicrobial activity on textile materials

Measurement uncertainty is widely recognized among physicists and chemists, but is a relatively new concept to many microbiologists. Generally, available documents about measurement uncertainty in microbiological testing are applicable to food and water microbiology. Two quantitative methods for evaluation of antimicrobial activity of textile materials are used commonly in textile laboratories. Methodology and expression of results for the two methods are similar; thus, calculation and expression of measurement uncertainty for results obtained by these test methods are also similar. This contribution describes the way in which measurement uncetainty for these methods can be evaluated and reported.

APLAC Interpretation and Guidance on the Estimation of Uncertainty of Measurement in Testing

The Asia Pacific Laboratory Accreditation Cooperation (APLAC) is the organization representing the community of bodies that accredit testing and calibration laboratories throughout the Asia Pacific region, including China and North America. APLAC members assess the competence of laboratories and grant them accreditation. They also provide mutual recognition of the equivalence of their accreditations, which facilitates international trade and acceptance by regulators. Harmonization of accreditation requirements is therefore vital to maintaining Mutual Recognition Arrangements. APLAC establishes management and technical criteria for accreditation and publishes guidance documents for accreditation bodies and laboratories.

Introducing the concept of uncertainty of measurement in testing in association with the application of the standard ISO/IEC 17025

ISO/IEC 17025 requests laboratories to estimate the overall uncertainty associated with a test result. In many cases this means a new requirement to laboratories. It is essential to understand the importance of the knowledge of the uncertainty of measurements as well as the principle that not always the smallest possible uncertainty is needed, but fitness for purpose has to be achieved. The paper suggests a policy on the implementation of the concept of uncertainty and guidance on how to proceed, taking into account the present state of the art of understanding the problem.