• Journal of Korean Society for Quality Management
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• v.30 no.1
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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.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.160-171
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• 2003

Criteria for the comparison of quality of asset portfolio management are risk and return. In this paper a method to use structural time-series model to determine an optimal portfolio for the improvement of quality of asset portfolio management is suggested. In traditional mean variance analysis expected return is assumed to be time-invariant. However, it is more realistic to assume that expected return is temporally dynamic and structural time-series model can be used to reflect time-varying nature of return. A data set from an insurance company was used to show validity of suggested method.

• Journal of Environmental Health Sciences
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• v.31 no.6
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• pp.489-497
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• 2005

A numerical method for the mathematical water modeling in 2-dimensional flow has been developed. The model based on a split operator technique, in which, the advection term is calculated using the upwind scheme. The diffusion term is one- dimensionalized and calculated using Crank-Nicholson's implicit finite difference scheme to reduce the numerical errors from large time steps and variable spacings. It also provides a relatively simple and economic method for more accurate simulation of pollutant dispersion. Water depths and flow velocities in the Boreyong reservoir during the normal water periods were predicted by numerical experiments with a 2-dimensional flow model so as to provide current field data for the study of advection and diffusion of pollutants. Developed 2-dimensional water quality model is applied to Boreyong reservoir to simulate a spatial and periodical changes of water quality.

• Journal of Korean Society for Quality Management
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• v.35 no.1
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• pp.61-72
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• 2007

The purpose of this research is to identify causalities among service quality, service value, customer satisfaction and customer loyalty. A Structural Equation Model is used to test the hypothesis of conceptual model. To test the model, we collect data by conducting a survey with 508 patients. Empirical result indicates that three factors such as tangibles, assurance, and empathy have direct impact on service value and customer satisfaction. Especially, customer loyalty is positively related not with service value but with customer satisfaction.

• The Journal of Industrial Distribution & Business
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• v.10 no.7
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• pp.71-82
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• 2019

Purpose - This study aims to identify the priorities of medical service quality improvement by customer satisfaction characteristics and potential customer satisfaction improvement (PCSI) index based on the dualistic quality classification of Kano Model (1984) for Comprehensive Health Screeening Center in General Hospitals and Centers only for Comprehensive Health Screening and suggest a direction for future improvement. Research design, data, and methodology - Through advanced research on health screening medical service quality, this study set four service quality factors, including tangible, human, process and supportive factors, and 39 measurement items. Based on these items, the study used 117 questions, which consist of dualistic quality factors, customer satisfaction coefficients, positive and negative questions for PCSI index and questions for current satisfaction. 300 effective samples were collected for adults in their 20s who experienced health screening service in Seoul, Gyeonggi-do and Incheon within the past two years. Collected data were input in the quality evaluation duality table to categorize quality factors and calculate customer satisfaction coefficients by Timko(1993). The study also analyzed PCSI index in comparison with current satisfaction and identified priorities in quality improvement. Results - It was found that the most urgent factors to improve the quality in both groups were adequate waiting hours and emergency response for complications, which are process factors classified as unitary quality. It is urgently needed to improve the quality as the PCSI index was high in supportive factors (complaint response team) as attractive quality in Comprehensive Health Screening Center in General Hospitals and in process factors (prevention of infection) as unitary quality in Centers only for Comprehensive Health Screening. As the PCSI index was low in space use as a tangible factor, it was found that the current level can be maintained instead of improvement. Conclusions - To improve the health screening medical service quality, it is required to focus on process factors (adequate waiting hours, emergency response for complications, prevention of infection) and supportive factors (complaint response team) among service qualities perceived by users. It is proposed to ensure continuous efforts to manage and reinforce priorities as a direction for future improvement in health screening service.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.421-431
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• 2021

Purpose: For improving outgoing quality, this study presents a novel sampling framework based on predictive analytics. Methods: The proposed framework is composed of three steps. The first step is the variable selection. The knowledge-based and data-driven approaches are employed to select important variables. The second step is the model learning. In this step, we consider the supervised classification methods, the anomaly detection methods, and the rule-based methods. The applying model is the third step. This step includes the all processes to be enabled on real-time prediction. Each prediction model classifies a product as a target sample or random sample. Thereafter intensive quality inspections are executed on the specified target samples. Results: The inspection data of three Samsung products (mobile, TV, refrigerator) are used to check functional defects in the product by utilizing the proposed method. The results demonstrate that using target sampling is more effective and efficient than random sampling. Conclusion: The results of this paper show that the proposed method can efficiently detect products that have the possibilities of user's defect in the lot. Additionally our study can guide practitioners on how to easily detect defective products using stratified sampling

• Korean Journal of Health Education and Promotion
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• v.30 no.5
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• pp.139-151
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• 2013

Objectives: This study investigated how income, duration of illness, social stigma, quality of sleeping, ADL and social participation related to Parkinson's disease(PD) predict depression in a conceptual model based on the International Classification of Functioning(ICF) model. Methods: The sample included 206 adults with idiopathic Parkinson's disease(IPD) attending D university hospital in B Metro-politan City. A structured questionnaire was used and conducted face-to-face interviews. The collected data were analyzed for fitness, using the AMOS 18.0 program. Results: A path analysis showed that the overall model provided empirical evidence for linkages in the ICF model. Depression was manifested by significant direct effects of social stigma(${\beta}=.20$, p<.001), quality of sleeping(${\beta}=-.40$, p<.001), ADL(${\beta}=-.20$, p<.01), and social participation(${\beta}=-.12$, p<.05), indirect effects including income(p<.05), duration of illness(p<.05). These variables explained 45.9% of variance in the prediction model. Conclusions: This model may help nurses to collect and assess information to develop intervention program for depression.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.709-725
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• 1998

The characteristics of storm and water quality are investigated based on the measuring data of the test river, the Hongje. the water quality of the test river is generally good comparing to other urban rivers in Seoul, because of the interception of sewer flow. But this system makes the river dry up for 3-4 months in winter. On the other hand, in rainy period the storm from the combined sewer system causes rapid increasing pollutants loads. In order to simulate the urban storm and water quality of the trest basin, the models such as SWMM, ILLUDAS, STORM, HEC-1 were applied and the results are compared in its applicability and accuracy aspects. All models discussed here have shown good results and it seems that SUMM is the most effective model in simulating both quantity and quality. Also, regression relations between the water quantity and quality were derived and their applicabilities were discussed. This regression model is a simple effective tool for estimating the pollutant loads in the rainy period, but if the amount of discharge is bigger than measuring range of raw data, the accuracy becomes poor. This model could be supplemented by expanding the range of collecting data and introducing the river characteristics. The HEC-1 would be anther effective model to simulate storm runoff of a river basin including urban area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.7-17
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• 2017

Loan consultants assist clients with loan application processing and loan decisions. Their duties may include contacting people to ask if they want a loan, meeting with loan applicants and explaining different loan options. We studied the efficiency of service quality of loan consultants contracted to a bank in Korea. They do not work as a team, but do work independently. Since he/she is not an employee of the bank, the consultant is paid solely in proportion to how much he/she sell loans. In this study, a consultant is considered as a decision making unit (DMU) in the DEA (Data Envelopment Analysis) model. We use a principal component analysis-data envelopment analysis (PCA-DEA) model integrated with Shannon's Entropy to evaluate quality efficiency of the consultants. We adopt a three-stage process to calculate the efficiency of service quality of the consultants. In the first stage, we use PCA to obtain 6 synthetic indicators, including 4 input indicators and 2 output indicators, from survey results in which questionnaire items are constructed on the basis of SERVQUAL model. In the second stage, 3 DEA models allowing negative values are used to calculate the relative efficiency of each DMU. In the third stage, the weight of each result is calculated on the basis of Shannon's Entropy theory, and then we generate a comprehensive efficiency score using it. An example illustrates the proposed process of evaluating the relative quality efficiency of the loan consultants and how to use the efficiency to improve the service quality of the consultants.

• Journal of Korean Society for Quality Management
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• v.52 no.2
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• pp.185-199
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• 2024

Purpose: The improvement of yield and quality in product manufacturing is crucial from the perspective of process management. Controlling key variables within the process is essential for enhancing the quality of the produced items. In this study, we aim to identify key variables influencing product defects and facilitate quality enhancement in CNC machining process using SHAP(SHapley Additive exPlanations) Methods: Firstly, we conduct model training using boosting algorithm-based models such as AdaBoost, GBM, XGBoost, LightGBM, and CatBoost. The CNC machining process data is divided into training data and test data at a ratio 9:1 for model training and test experiments. Subsequently, we select a model with excellent Accuracy and F1-score performance and apply SHAP to extract variables influencing defects in the CNC machining process. Results: By comparing the performances of different models, the selected CatBoost model demonstrated an Accuracy of 97% and an F1-score of 95%. Using Shapley Value, we extract key variables that positively of negatively impact the dependent variable(good/defective product). We identify variables with relatively low importance, suggesting variables that should be prioritized for management. Conclusion: The extraction of key variables using SHAP provides explanatory power distinct from traditional machine learning techniques. This study holds significance in identifying key variables that should be prioritized for management in CNC machining process. It is expected to contribute to enhancing the production quality of the CNC machining process.