• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.625-632
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• 2006

A Datawarehouse, which extracts and saves the massive analysis data from the operating servers, is a decision support tool in which data quality and processing time are very important. Thus, it is necessary to standardize and improve datawarehouse development process in order to stabilize data quality and improve the productivity. We propose a novel improved process for datawarehouse development by applying the configuration management of CMMI (Capability Maturity Model Integration) which has become a major force in software development process improvement. In addition, we specify some matrices for evaluating datawarehouse development process. Through the comparison analysis with other existing processes, we show that our proposal is more efficient in cost and productivity as well as improves data quality and reusability.

• Journal of Korean Society for Quality Management
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• v.19 no.1
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• pp.65-71
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• 1991

According to characters of software, the methods of evaluating reliability are different. The purpose of this study was to develop application software used in the field and to set up reliability model which failure density was used so that in the process of test, developer and user may apply a point of time to field business and to apply developed model which real data use used.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• Information Systems Review
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• v.6 no.2
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• pp.195-208
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• 2004

In this paper we propose a new software project development management model incorporating quality management to schedule management. Though many efficient techniques such as code review and inspection are used to remove defects, the effect of defect removal time on project schedule hasn't been studied much. However, poor quality management has an important effect upon overall schedule and sometimes software projects fails due to it. Thus, quality management and schedule management should be considered together and we need to reflect the time to maintain software quality into the schedule management. For the proposed model we introduced "Quality Value" representing the needed time to remove software defects. We assume PSP/TSP to gather the needed data for quality value. The proposed model can be used to predict the effect of software defects on schedule in advance and to prevent schedule lag.

• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.599-614
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• 2012

Purpose: We measure service quality based on service process, and examine relationships among product quality, product and service loyalty. Methods: We develop a construct to evaluate process based service quality. We collect data from customers of auto maintenance centers to measure perceived product quality, service and product quality. We test relationships between constructs using structural equation model and regression analysis. Results: Relationships among perceived-product quality, service quality, service loyalty, and product loyalty are all significant. Conclusion: Perceived-product quality has a indirect impact through service quality and loyalty in addition to a direct impact on product loyalty.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.84-92
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• 2004

A process control procedure is proposed when 100% inspection is performed in a process with excellent capability. Only the incomplete measurement data is assumed to be available, i.e. the specific measurement value of the quality characteristic is not available for each item but it can be determined to be smaller or larger than any prescribed value. In the suggested model, a signal limit is introduced to determine whether the process under study is in control or not. If the quality characteristic of an incoming item exceeds the upper signal or the lower signal limit, the process is determined to be stopped or not by comparing the number of consecutively accepted items with a predetermined threshold number. The procedure is designed based on the type I and II errors. The performance of the model is evaluated by the expected number of items produced under the in-control and out-of-control states until the process is stopped.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.520-538
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• 2019

In this study, it was proposed that a method of setting the target water quality for TOC using the watershed model and the load duration curves to manage non-biodegradable organics in the total water load management system. To simulate runoff and water quality of the watershed, the HSPF model is used which is appropriate for urban and rural areas. Additionally, the load duration curve is used to reflect the variable water quality correlated with various river flow rates in preparing the TMDL plans in the U.S. First, the model was constructed by inputting the loads calculated from the pollutant sources in 2015. After the calibration and verification process, the water quality by flow conditions was analyzed from the BOD and TOC simulation results. When the BOD achieved the target water quality by inputting the target year loads for 2020, the median and average values of TOC were proposed for the target water quality. The provisional method of TOC target water quality for the management of non-biodegradable organics, which is one of the challenges of the total water load management system, was considered. In the future, it is expected to be used as basic data for the conversion of BOD into TOC in the total water load management system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1101-1106
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• 2005

The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Operating data (trace parameters) were collected on-line but quality data (measurement parameters) were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Thus, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were employed for data generation, and then modeling was accomplished, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to the control parameters. The dynamic polynomial neural network (DPNN) was used for data modeling that used the ingot fabrication data.

• Journal of Korean Society for Quality Management
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• v.45 no.2
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• pp.209-225
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• 2017

Purpose: Since traditional p chart is unable to deal with the variation of attribute data, this paper proposes a new attribute control chart for nonconforming proportions incorporating overdispersion with a beta-binomial model. Methods: Statistical theories for control chart developed under the beta-binomial model and a new approach using this control chart are presented Results: False alarm probabilities of p chart with the beta-binomial model are evaluated and demerits of p chart under overdispersion are discussed from three examples. Hence a concrete procedure for the proposed control chart is provided and illustrated with examples Conclusion: The proposed chart is more useful than traditional p chart, individual chart to treat observed proportions nonconforming as variable data and Laney p' chart.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.92-102
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• 2004

In this era of intense competition, TQM has become the key program in organizations as they strive for a competitive advantage. It has been applied to manufacturing and service sector since BNQA model was established in 1987. TQM literature for manufacturing sector abounds with empirical studies on the critical dimensions of TQM, but there is few empirical studies on the TQM evaluation for service sector. In this paper, two methodologies are applied to evaluate the TQM activities of service companies comparatively One of them is the traditional scoring system(TSS) by analytic hierarchy process(AHP). The other is the efficiency measuring system(EMS) by data envelopment analysis(DEA). DEA outperformed other alternative methods to measure the efficiency and it can be applied to evaluate the TQM activities. The objective of this paper is to evaluate TQM activities of domestic service companies by applying TAE(Total quality management Activities Evaluation) model to them. The result of this study is that TSS scores are not significantly correlated with EMS scores. It means that service organizations must not only make efforts to get the higher scores in terms of TSS but also take necessary steps to enhance their efficiencies.