Guide for Conducting a Repeatability and Reproducibility Study on Test Equipment for Nondestructive Testing

2011 ◽  
Author(s):  
Keyword(s):  
Nondestructive Testing ◽  
Test Equipment ◽  
Reproducibility Study ◽  
Repeatability And Reproducibility

scholarly journals Assessment of the Adequacy of Gauge Repeatability and Reproducibility Study Using a Monte Carlo Simulation

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Chunghun Ha ◽  
David S. Kim ◽  
SeJoon Park
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
System Analysis ◽  
Performance Metrics ◽  
Repeated Measurements ◽  
Percentage Error ◽  
Nested Design ◽  
Reproducibility Study ◽  
Measurement System Analysis ◽  
Repeatability And Reproducibility

ANOVA gauge repeatability and reproducibility study is the most popular tool for measurement system analysis. Two experimental designs can be applied depending on the durability of the objects. If repeated measurements are possible or sufficient homogeneous nonrepeatable samples are available, crossed design is appropriate; otherwise, nested design should be used. In this paper, we investigated the adequacy of ANOVA gauge repeatability and reproducibility study from the perspective of practitioners. We proposed a Monte Carlo simulation that is close to the realistic procedure to evaluate the adequacy of both structures. During the evaluation, we considered the average performance metrics, percentage of correct decision, histogram shape, and symmetric mean absolute percentage error for the four popular performance metrics, namely, % Study Variation, % Contribution, % Tolerance, and the number of distinct categories. The experimental results show that the nested design fails to judge the precision of the gauge while the crossed design succeeds.

Measuring Uncertainty Using Different Approaches: A Case Study for Acetaminophen Quantification

2016 ◽  
Vol 99 (3) ◽  
pp. 612-617 ◽  
Author(s):  
Fabiane Lacerda Francisco ◽  
Alessandro Morais Saviano ◽  
Felipe Rebello Lourenço
Keyword(s):  
Measurement Uncertainty ◽  
Uncertainty Estimation ◽  
Pharmaceutical Drug ◽  
Drug Products ◽  
Pharmaceutical Equivalence ◽  
Reproducibility Study ◽  
Repeatability And Reproducibility ◽  
Analytical Result ◽  
Measurement Uncertainty Estimation

Abstract Investigation of out-of-specification analytical results is laborious, time-consuming, and costly and must be well documented. However, an analytical result is not complete unless reported with its measurement uncertainty. Here, we compare four different approaches for measurement uncertainty estimation used in acetaminophen quantification in pharmaceutical drug products. Measurement uncertainties were estimated using a repeatability and reproducibility study, Eurachem/Citac guidelines, Monte Carlo simulations, and a spreadsheet method. These different approaches provided similar results. However, they differed by the sources of uncertainties considered, by the procedures of calculation, and by the effort required in routine applications. Nevertheless, all four approaches were successful in assessing conformity of acetaminophen content in pharmaceutical drug products and may be used in assessing pharmaceutical equivalence.

scholarly journals Effect of Non-Fulfillment of Assumptions on Gage Repeatability and Reproducibility Study Evaluation

2019 ◽  
Vol 1 (1) ◽  
pp. 472-478
Author(s):  
Pavel Klaput ◽  
David Vykydal ◽  
Jiří Plura
Keyword(s):  
Measurement System ◽  
Simulated Data ◽  
Statistical Properties ◽  
System Quality ◽  
Measurement Systems ◽  
Basic Assumptions ◽  
Reproducibility Study ◽  
Study Evaluation ◽  
Measurement Systems Analysis ◽  
Repeatability And Reproducibility

Abstract The evaluation of the measurement system quality has already become an integral part of quality planning activities in both the automotive and metallurgical industries. An important assumption for obtaining the most relia ble results is compliance with the basic assumptions for evaluating the variability of the measurement system. The main goal of this paper is to analyze, how the failure to meet the basic assumptions influences the evaluation of the measurement system's statistical properties. This goal is achieved by performing a detailed analysis of the latest developments in the field of measurement systems analysis aimed at verifying the assumptions of normality and uniformity. The evaluation of the effect of non-fulfillment of both assumptions on the values of the most important statistical properties of the measurement system is performed using simulated data. Suitable graphical tools are used for practical verification of both assumptions.

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