• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.200-205
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• 2000

An economic process monitoring procedure is presented using a surrogate variable for the case where performance variable is dichotomous. Every item is inspected with a surrogate variable and determined whether it should be accepted or rejected. When an item is rejected, the previous number of consecutively accepted items is compared with a predetermined number r to decide whether there is a shift in fraction nonconforming or not. The conditional distribution of the surrogate variable given the performance variable is assumed to be normal. A cost model is constructed which includes costs of inspection, misclassification, illegal signal, undetected out-of-control state, and correction. Methods of finding the optimum number r and screening limit are provided. Numerical studies on the effects of cost coefficients are also performed.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.1-15
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• 2019

Purpose: The purpose of this study is to support SMEs' introduction of smart factories during the $4^{th}$ Industrial Revolution era. Through this study, we developed the readiness assessment framework for SMEs. This study draws practical implications for improving the readiness of SMEs to introduce smart factories. Methods: Readiness Assessment Framework Design method, Case Studies Analysis Results: This study identified SMEs suitable for smart factories and identified key issues for nonconforming companies. And the diagnostic framework has been determined whether it works in a real-life SME environment. Conclusion: In order to succeed in the smart factory deployment, readiness assessment for SMEs should be performed as necessary. Prior to the introduction of smart factories, quality innovation activities should be carried out according to factory level.

• Journal of Construction Engineering and Project Management
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• v.8 no.1
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• pp.1-9
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• 2018

US transportation agencies are dealing with shrinking budgets, limited work forces, and deteriorating infrastructure. In order to cope with funding uncertainty, state highway agencies are now looking into their own organizations and identifying programs, practices, and processes that have potential for cost saving. A quality assurance (QA) program is an integral part of highway construction and ensures a project's contracted level of quality. The cost of quality (conforming and nonconforming) can constitute a sizable part of total construction cost. As the quality assurance programs evolved, various practices and processes were developed over time and later adopted by state highway agencies. These practices and processes include different QA standards and specifications, varying testing methods, central testing lab vs. on site testing, performance based vs. prescribed quality assurance practices, implementation of innovative quality assurance practices, etc. Therefore, there is an opportunity to assess different QA strategies and recommend those practices that are effective and cost efficient. A national survey was conducted by the authors, which provided a detailed mapping of various QA practices and processes used as part of QA programs and identified areas where agencies can focus on for cost savings. The survey found that QA sampling and testing plans, optimization of sampling plans, optimization of QA standards and specifications, and implementation of innovative test methods and processes are the main areas the agencies should focus to lean the current QA programs.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.41-50
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• 1994

Consider a canning process where cans are filled with an expensive ingredient. Cans weighting above the specified limit are sold in a regular market for a fixed price, and underfilled cans are emptied and refilled at the expense of a reprocessing cost. In this paper, the effect of measurement error on the determination of the optimal process mean for a canning process is examined. It is assumed that the quantity X of ingredient in a can is normally distributed with unknown mean and known variance, and the observed value Y of X is also normally distributed with known mean and variance. A profit model is constructed which involves selling price. cost of ingredients, reprocessing cost. and cost from an accepted nonconforming can, and methods of finding the optimal process mean and the cutoff value on Y are presented. It is shown that the optimal process mean increases. and the expected profit decreases when the measurement error is relatively large in comparison to the process variance.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.7
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• pp.1030-1040
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• 1998

One of the main unresolved issues in large-eddy simulation(LES) of wall-bounded turbulent flows is the requirement of high spatial resolution in the near-wall region, especially in the spanwise direction. Such high resolution required in the near-wall region is generally used throughout the computational domain, making simulations of high Reynolds number, complex-geometry flows prohibitive. A grid-embedding strategy using a nonconforming spectral domain-decomposition method is proposed to address this limitation. This method provides an efficient way of clustering grid points in the near-wall region with spectral accuracy. LES of transitional and turbulent channel flow has been performed to evaluate the proposed grid-embedding technique. The computational domain is divided into three subdomains to resolve the near-wall regions in the spanwise direction. Spectral patching collocation methods are used for the grid-embedding and appropriate conditions are suggested for the interface matching. Results of LES using the grid-embedding strategy are promising compared to LES of global spectral method and direct numerical simulation. Overall, the results show that the spectral domain-decomposition grid-embedding technique provides an efficient method for resolving the near-wall region in LES of complex flows of engineering interest, allowing significant savings in the computational CPU and memory.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.619-632
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• 2023

Purpose: The main function of INS (Inertial Navigation System) is to measure the position of an armed vehicle and its performance is confirmed through the positioning accuracy test of Korean Defense Standards (KDS). The current standards, however, do not provide clear test methods and the conditions for performing positioning accuracy tests. Accordingly, the purpose of this study is to develop a new method for positioning accuracy test which would be effective. Methods: In this study, a new INS positioning accuracy test method is suggested based on the analysis of test data collected through a statistical experiment known as central composite design. For the positioning accuracy experiment of K105A1, a self-propelled artillery, two factors of driving velocity and driving distance are considered. Results: Based on the analysis of experimental data, a regression model for the positioning error is fitted and the positioning accuracy test of INS is so developed to maximize the positioning error. The standard proximity rate is used as an additional test criterion to evaluate the performance level of INS. Conclusion: The proposed new positioning accuracy test for INS has the advantage of finding the nonconforming items effectively. It is also expected to be utilized for the other similar INS positioning accuracy tests.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.5
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• pp.267-275
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• 2022

Using a nonconforming mesh in enrichment methods results in several numerical issues induced by discontinuities and singularities found within the solution spaces, including the computational overhead during integration. In this study, we present a novel enrichment technique based on the selective expansion technique of moment fitting (Düster and Allix, 2020). In particular, two modifications are proposed to address the inefficiency during the integration process. First, a feedforward artificial neural network is introduced to correlate the implicit functions and integration moments. Through numerical examples, it is shown that the efficiency of the method is greatly improved when compared with existing expansion techniques, whereas the solution accuracy is maintained. Additionally, the finite element and domain representation grids are separated, which in turn improves the solution accuracy even for coarse mesh conditions.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.