• 품질경영학회지
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• 제30권1호
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• pp.1-21
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• 2002

The purpose of this study was to empirically examine the customer oriented quality creation by considering quality elements required by customers in the product design process. The study tried to extract attractive quality elements by using Kano's model. After identifying the elements HOQ(the house of quality) of QFD(quality function deployment) was used to identify the trend of quality elements evaluation. Test for equal means (t-test) was applied to verify the attractive quality elements of adult shoes. It made us find the customer oriented quality elements from the customer needs and latent dissatisfaction. We collected the opinions of experts on shoes and complete the cause and effect diagram and affinity diagram (KJ method). The data of the questionnaire was put to the QFD and the contents of quality elements was identified by brain storming method. We calculated indexes which were the multiplication of weight and marks of quality elements in the cross table of the HOQ by QFD. Then we tested for the equality of means between the indexes and the sum of attractive quality elements. The results for equal means were statistically significant. To create the customer quality the product design should be differentiated between the age groups over attractive quality elements.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2007년도 춘계학술대회
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• pp.302-309
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• 2007

To conduct statistical process control needs the assumption that the process data are independent. However, most of chemical processes, like a semi-conduct processes do not satisfy the assumption because of autocorrelation. It causes abnormal out of control signal in the process control and misleading process capability. In this study, we introduce that Shore's method to solve the problem and to find the optimal subgroup size to estimate variance for AR(l) model. Especially, we focus on finding an actual subgroup size for small samples using simulation. It may be very useful for statistical process control to analyze process capability and to make a Shewhart chart properly.

• 품질경영학회지
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• 제37권3호
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• pp.33-38
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• 2009

When we estimate the parameters of software reliability models, we usually use maximum liklihood estimator(MLE). But this method is required a large data set. In particular, when we want to estimate it with small observed data such as early stages of testing, we give rise to the non-existence of MLE. Therefore, it is interesting to look into the influence of parameter estimators obtained using MLE. In this paper, we use two non-homogenous poisson process software reliability growth model: delayed S-shaped model and log power model. In this paper, we calculate the sensitivity of estimators about failure intensity function for two SRGMs respectively.

• 품질경영학회지
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• 제45권4호
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• pp.629-648
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• 2017

Purpose: The world faces a great turning point fundamentally rebuilding the future, and human lives, by embracing the 4th industrial revolution era. This paper aims to seek new and various business models in the 4th industrial revolution era, and to examine the evolution of quality management in the changing of the industrial ecosystem. Methods: This paper examines the various strategies of approaching the 4th industrial revolution in Germany, the USA, Japan, China, and Korea. This paper also draws detailed items by classifying the six major items of Malcolm Baldridge into large, medium, and small scale classifications, researches items from the technical perspective by applied fields, and the four major factor perspectives of quality management, as well as analyzes the relevant items in a multidimensional method. After a questionnaire survey targeting 200 quality experts was conducted, the important quality management factors were selected by applying the Analytic Hierarchy Process (AHP) method. Results: The importance of the general criteria was analyzed in the order of customers, MAKM (measurement, analysis, and knowledge management), workforce, strategy, operations, and leadership. As for the importance analysis results of the secondary subcriteria, the following items are highly analyzed: senior leadership, searching business model's innovation opportunity, customer satisfaction improvement, big data utilization, systematic management of workforce, and, planning and design quality. Conclusion: In the era of the Internet of everything, when complexity increases, this study presented a quality management direction suitable for new business methods challenging existing orders by drawing on quality management priorities.

• 한국멀티미디어학회논문지
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• 제25권7호
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• pp.903-911
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• 2022

A shrimp quality detection model using YOLOv4 deep learning algorithm is designed, which is superior in terms of network architecture, data processing and feature extraction. The shrimp images were taken and data expanded on their own, the LableImage platform was used for data annotation, and the network model was trained under the Darknet framework. Through comparison, the final performance of the model was all higher than other common target detection models, and its detection accuracy reached 93.7% with an average detection time of 47 ms, indicating that the method can effectively detect the quality of shrimp in the production process.

• 품질경영학회지
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• 제49권2호
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.

• 디지털융복합연구
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• 제10권11호
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• pp.11-27
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• 2012

본 연구의 목적은 외부 IT감리의 핵심 성공 요인을 제시하는 것이다. 이를 위해, 정보시스템 성공 모형과 서비스 품질 개념을 기반으로 통합 모델을 제시하였다. 연구모형은 외부 감리를 수행한 경험이 있는 국내 공공기관을 표본으로 총 254개의 데이터를 수집하여 분석하였다. 분석결과 서비스 품질 특성 중 응답성, 신뢰성, 유형성은 정보시스템의 구현 프로세스 품질에 유의한 영향을 미치는 것으로 나타났다. 또한 프로세스 품질은 정보시스템 구현 성공(시스템 품질)에 유의한 영향을 미치는 것으로 나타났다.

• 대한산업공학회지
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• 제40권3호
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• pp.257-266
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• 2014

The semiconductor manufacturing industry is managed by a number of parameters from the FAB which is the initial step of production to package test which is the final step of production. Various methods for prediction for the quality and yield are required to reduce the production costs caused by a complicated manufacturing process. In order to increase the accuracy of quality prediction, we have to extract the significant features from the large amount of data. In this study, we propose the method for extracting feature from the cell level data of probe test process using OPTICS which is one of the density-based clustering to improve the prediction accuracy of the quality of the assembled chips that will be placed in a package test. Two features extracted by using OPTICS are used as input variables of quality prediction model because of having position information of the cell defect. The package test progress for chips classified to the correct quality grade by performing the improved prediction method is expected to bring the effect of reducing production costs.

• 품질경영학회지
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• 제26권4호
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• pp.111-123
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• 1998

We consider the problem of modeling count data where the observation period is determined by the life time of the system under study. We assume random effects or a frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect or a frailty, the death times follow a Weibull distribution with a hazard rate. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time. A gamma distribution is assumed for the frailty model. Maximum likelihood estimators of the model parameters are obtained. A model for the time to death and the number of failures system received is constructed and consequences of the model are examined.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.313-322
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• 2016

Purpose: We introduce ways to employ Markov chain model to evaluate the effect of preventive maintenance process. While the preventive maintenance process decreases the failure rate of each subsystems, it increases the downtime of the system because the system can not work during the maintenance process. The goal of this paper is to introduce ways to analyze this trade-off. Methods: Markov chain models are employed. We derive the availability of the system consisting of N repairable subsystems by the methods under various maintenance policies. Results: To validate our methods, we apply our models to the real maintenance data reports of military truck. The error between the model and the data was about 1%. Conclusion: The models developed in this paper fit real data well. These techniques can be applied to calculate the availability under various preventive maintenance policies.