• IE interfaces
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• v.18 no.4
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• pp.444-453
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• 2005

The purpose of the Gage R&R study is to determine whether a measurement system is adequate for monitoring a process. If the measurement system variation is small relative to the process variation, then the measurement system is deemed "adequate". The sources of variation associated with the measurement system are compared using an analysis of variance (ANOVA) model, in general. A typical ANOVA model used in a standard Gage R&R study is the two-factor random effect model. Then, the ANOVA partitions the total variation into three categories: repeatability, reproducibility, part variation. However, if the process variation possesses the between group variation, within group variation, and within part variation, these variations can cause the measurement system evaluation to provide misleading results. That is, in the standard Gage R&R study these variations affect the estimate of repeatability, reproducibility, or both. This paper presents a four-factor nested factorial ANOVA model which explicitly considers these variations for the Gage R&R study. The variance component estimators are derived by setting the EMS equations equal to the corresponding mean square from the ANOVA table and solving. And the proposed model is compared with the standard Gage R&R model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.55
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• pp.13-24
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• 2000

6 sigma movement is the most prominent quality improvement methodology in practice. Measurement plays an important role in helping any organization improve quality. Therefore, the measurement systems analysis is the first step for the quality improvement of manufacturing process in 6 sigma movement. In this study, we investigate the effect of Gage Repeatability and Reproducibility(Gage R&R) in view of defect rate and process capability indices, and provide guidelines for acceptance of gage repeatability and reproducibility(%R&R) for six sigma quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.129-135
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• 2012

Companies strive for quality improvement and use process data obtained through measurement process to monitor and control the process. Measurement data contain variation due to error of operator and instrument. The total variation is sum of product variation and measurement variation. Gage R&R is for repeatability and reproducibility of measurement system. Gage R&R study is usually conducted to analyze the measurement process. In performing the gage R&R study, several parameters such as the appropriate number of operators (o), sample size of parts (p), and replicate (r) are used. In this paper we propose how to determine the optimal combination of number of operators (o), sample size of parts (p), and replicates (r) considering measurement time and cost by statistical method.

• Journal of Korean Society for Quality Management
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• v.44 no.1
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• pp.77-94
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• 2016

Purpose: This paper reviews Type 1 Gage study, Gage R&R study, and procedure of ISO 22514-7 for assessing a measurement system, and discusses some relationships between the measurement capability indices. Methods: The gage capability index $C_g$ of Type 1 Gage study, precision-to-tolerance ratio PTR of Gage R&R study, and measurement performance ratio $Q_{MS}$ and $Q_{MP}$ of ISO 22514-7 are considered in this paper. Results: This paper derives the relationships between $C_g$ and $Q_{MS}$, PTR and $Q_{MP}$, and $Q_{MS}$ and $Q_{MP}$, respectively, and discusses the acceptance conditions for each procedures. Conclusion: The measurement capability analysis is the first step for the quality improvement of the manufacturing processes. Therefore the result of this study provides a helpful guidelines for assessing the measurement system, enabling proper evaluation of manufacturing processes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.975-982
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• 2005

The purpose of the Gage R&R study is to determine whether a measurement system is adequate for monitoring a process. If the measurement system variation is small relative to the process variation, then the measurement system is deemed 'adequate'. The sources of variation associated with the measurement system are compared using an analysis of variance (ANOVA) model, in general. A typical ANOVA model used in a standard Gage R&R study is the two-factor random effect model. Then, the ANOVA partitions the total variation into three categories: repeatability, reproducibility, part variation. However, if the process variation possesses the between group variation, within group variation, and within-part variation, these variations can cause the measurement system evaluation to provide misleading results. That is, in the standard Gage R&R study these variations affect the estimate of repeatability, reproducibility, or both. This paper presents a four-factor nested factorial ANOVA model which explicitly considers these variations for the Gage R&R study. The variance component estimates are derived by setting the EMS equations equal to the corresponding mean square from the ANOVA table and solving. And the proposed model is compared with the standard Gage R&R model.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.211-221
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• 1998

It is very important to have a satisfactory measurement system, since it is useless to try to improve the manufacturing process without an adequate measurement system. Therefore, evaluation of the measurement system is the first step for the quality improvement of the manufacturing process. To estimate the measurement error we must conduct a controlled gage repeatability and reproducibility(gage R&R) study. Many manufacturers use a gage or instrument to measure multiple dimensions for the overall quality of the manufactured parts. In this case, it is necessary to estimate the gage R&R for multiple dimensions. When a gage measures a large number of dimensions of a part, it is very time-consuming and costly to measure all the dimensions. In this paper we propose the use of the principal component analysis method to identify a few principal components out of the original multivariate measurement capability to explain most of the measurement system variation pattern.

• Korean Journal of Acupuncture
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• v.24 no.4
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• pp.55-67
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• 2007

Objectives : The repeatability and reproducibility of MIR-2, a newly developed impedance measurement device (four electrode method) on skin are of the meridian system, is evaluated and a method to improve the reliability is discussed. Methods : Multiple gage R&R studies were conducted for the impedance measurements over bilateral KI3 acupoint in ten participants by three assessors using MIR-2 device. Gage R&R studies were repeated after controlling the acupoint locating method or one value correction by replacing one assessor's outlying value with an average of the other assessors' values to explore any feasibility of improvement of measurement reliability. Results : Controlling acupoint locating method and replacing one value with an average of other assessors' value led to improved variation metrics in a gage R&R study. Conclusions : Measurement reliability can be improved by controlling measurement procedures or by using repeated measurement method, which will facilitate development of clinically applicable measurement device with reliability.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.14 no.2
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• pp.75-84
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• 2010

Objectives: The objective of the current study is to determine whether an ultrasound device system is adequate for measuring distance from Sangwan (CV13) to pancreas. Methods: We recruited 3 healthy young male subjects and 2 sonographers. The each sonographer measured vertical shortest distance from CV13 to pancreas with a ultrasound device three times in random order. Because the total variation could be divided into repeatability, reproducibility and subject-to-subject variation in Gage R&R method, we compared the sources of variation associated with the measurement system with an analysis of variance model. Results & Conclusions: Number of distinct categories is calculated on the basis of standard deviation of subject-to-subject divided by standard deviation of total Gage R&R. If the number of categories is five or more, the measurement system may be acceptable for the analysis of the process. The number of distinct categories of the ultrasound device system for measuring distance from CV13 to pancreas was 6.29. So we concluded that repeatability and reproducibility of the ultrasound device system for measuring distance from CV13 to pancreas was acceptable.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.78-85
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• 2019

High variance observed in the measurement system can cause high process variation that can affect process capability badly. Therefore, measurement system analysis is closely related to process capability analysis. Generally, the evaluation for measurement system and process variance is performed separately in the industry. That is, the measurement system analysis is implemented before process monitoring, process capability and process performance analysis even though these analyses are closely related. This paper presents the effective concurrent evaluation procedure for measurement system analysis and process capability analysis using the table that contains Process Performance (Pp), Gage Repeatability & Reproducibility (%R&R) and Number of Distinct Categories (NDC). Furthermore, the long-term process capability index (Pp), which takes into account both gage variance and process variance, is used instead of the short-term process capability (Cp) considering only process variance. The long-term capability index can reflect well the relationship between the measurement system and process capability. The quality measurement and improvement guidelines by region scale are also described in detail. In conclusion, this research proposes the procedure that can execute the measurement system analysis and process capability analysis at the same time. The proposed procedure can contribute to reduction of the measurement staff's effort and to improvement of accurate evaluation.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.191-195
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• 2008

The present study contributes reviewing and suggesting various models for measurement system analysis (MSA). Measurement errors consist of accuracy, linearity, stability, part precision, repeatability and reproducibility (R&R). First, the major content presents split-plot design, and the combination method of crossed and nested design for obtaining gage R&R. Second, we propose $\bar{x}-s$ variable control chart for calculating the gage R&R and number of distinct category. Lastly, investigating the determination of gage performance curve which establishes the control specification propagating calibration uncertainties and measurement errors is described.