• Agribusiness and Information Management
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• v.3 no.1
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• pp.11-22
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• 2011

This study describes the development of a web-based system that collects all data generated in the research conducted to set pre-harvest residue limits (PHRLs) for agricultural product safety control. These data, including concentrations of pesticide residues, limit of detection, limit of quantitation, recoveries, weather charts, and growth rates, are incorporated into a database, a regression analysis of the data is performed using statistical techniques, and the PHRL for an agricultural product is automatically computed. The development and establishment of this system increased the efficiency and improved the reliability of the research in this area by standardizing the data and maintaining its accuracy without temporal or spatial limitations. The system permits automatic computation of the PHRL and a quick review of the goodness of fit of the regression model. By building and analyzing a database, it also allows data accumulated over the last 10 years to be utilized.

• Journal of Korean Society for Quality Management
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• v.34 no.1
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• pp.13-19
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• 2006

Data mining is a useful tool for analyzing data from different perspectives and for summarizing them into useful information. Recently, the data mining methods are applied to solving quality problems of the manufacturing processes. This paper discusses the problems of construction of a quality mining system, which is based on the various data mining methods. The quality mining system includes recipe optimization, significant difference test, finding critical processes, forecasting the yield. The contents and system of this paper are focused on the TFT-LCD manufacturing process. We also provide some illustrative field examples of the quality mining system.

• Quality Improvement in Health Care
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• v.8 no.2
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• pp.186-207
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• 2001

Background : This study presented an analysis of healthcare quality indicators using data mining and a development of decision support system for quality improvement. Method : Specifically, important factors influencing the key quality indicators were identified using a decision tree method for data mining based on 8,405 patients who discharged from a medical center during the period between December 1, 2000 and January 31, 2001. In addition, a decision support system was developed to analyze and monitor trends of these quality indicators using a Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. Result : Among 12 selected quality indicators, decision tree analysis was performed for 3 indicators ; unscheduled readmission due to the same or related condition, unscheduled return to intensive care unit, and inpatient mortality which have a volume bigger than 100 cases during the period. The optimum range of target group in healthcare quality indicators were identified from the gain chart. Important influencing factors for these 3 indicators were: diagnosis, attribute of the disease, and age of the patient in unscheduled returns to ICU group ; and length of stay, diagnosis, and belonging department in inpatient mortality group. Conclusion : We developed a decision support system through analysis of healthcare quality indicators and data mining technique which can be effectively implemented for utilization review and quality management in a healthcare organization. In the future, further number of quality indicators should be developed to effectively support a hospital-wide Continuous Quality Improvement activity. Through these endevours, a decision support system can be developed and the newly developed decision support system should be well integrated with the hospital Order Communication System to support concurrent review, utilization review, quality and risk management.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.173-187
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• 2022

A special government agency has been charged with implementing quality management to guarantee the quality of wild-simulated ginseng. However, these processes are carried out by use of documents, and this has resulted in information omission and high document management costs. To solve this problem, this study analyzed the existing quality management process by using a smart contract for the existing offline form and proposed a new quality management system for storing and managing all log data in the blockchain. This system reduced documentation management costs about quality management and recorded information in the previous step through the quality management steps, thus forming a step-by-step record chain. Experiments were conducted by implementing this system, which improved data integrity and reliability. Additionally, sensitive information, such as personal information, was included in the system by use of the off-chain technology.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.18-26
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• 2017

Defense industries which require high reliability need an optimized quality management system with well-planned implementation. And the government should examine the overall status of defense industries, then establish practical policies with a proper support plan in required areas to upgrade the quality management level of manufacturers. Thus, DTaQ developed the model for 2 years from 2014, which specialized in quality management level analysis for defense industries. And a survey has been undertaken with that model by DTaQ and Korea Research Center in 2016. The surveyed companies randomly sampled among those which have more than 30 employees and delivery history over past 3 years, and finally 106 defense industries were selected. This paper present survey method and indexes for survey of defense industry quality management level. The survey was conducted in the order of planning, data collection and data processing, and the validity and reliability of the data were verified to increase objectivity of survey results. The survey contents mainly consist of system quality and management quality. System quality includes Product Development Management, Production Operation Management, supply chain quality management, Safety & Environment Management and Reliability Management, on the other hand, management quality includes Strategic Leadership, Human Resource Management, Customer Market Management and Information & Knowledge Management. Thus this proposes the current overall quality management status of the 106 defense industries and shows level differences by company sizes and manufacturing sectors based on the result of survey. Specifically, this paper enables to track the areas which need prompt government support with the policy directions to make quality management level higher. Therefore, it is expected that this can be used as reference data in establishing quality policies for military supplies in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.31-47
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• 2003

Quality design in practice highly depends on human designer's intuition and past experiences due to lack of formal knowledge about the relationship among 10 variables. This paper represents an data mining approach for developing quality design support system that integrates Case Based Reasoning (CBR) and Artificial Neural Networks (ANN) to effectively support all the steps in quality design process. CBR stores design cases in a systematic way and retrieve them quickly and accurately. ANN predicts the resulting quality attributes of design alternatives that are generated from CBR's adaptation process. When the predicted attributes fail to meet the target values, quality design simulation starts to further adapt the alternatives to the customer's new orders. To implement the quality design simulation, this paper suggests (1) the data screening method based on ξ-$\delta$ Ball to obtain the robust ANN models from the large production data bases, (2) the procedure of quality design simulation using ANN and (3) model management system that helps users find the appropriate one from the ANN model base. The integration of CBR and ANN provides quality design engineers the way that produces consistent and reliable design solutions in the remarkably reduced time.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.63-70
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• 2006

This study aims to development of web-based process management system for spatial data construction. For developing this system work classification of basic surveying was standardized and quality management method for spatial data was established. Production process and work classification system for basic surveying such as control point surveying using GPS, leveling, aerial photographing, digital mapping, topographic mapping, digital elevation modeling, aerial photographic DB construction and digital orthophotomap was standardized. The status of the output and quality inspection for basic surveying project were analyzed, and the elements of quality inspection and data format for the type of outputs were analyzed. Based on standardized and analyzed contents, web-based process management system was developed after database and process was designed. The process management system consisted of process management, quality control, metadata management, and system management.

• Journal of Korean Society for Quality Management
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• v.22 no.3
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• pp.152-160
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• 1994

This paper concerns an expert system for reliability management. The system includes data base, life data analysis, life testing sampling plans and system operation. PROLOG is used as a language with dBASE III+ for the data base management system and C for calculations and graphics. This system analyzing the data and selecting an appropriate sampling plan can be implemented on an IBM PC 386 or a higher level machine.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• Journal of Korean Society for Quality Management
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• v.32 no.2
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• pp.168-190
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• 2004

In these days of world-wide business environment, the characteristics of quality management are variety, specialty, decentralization, totality, etc. Thus nowadays quality management is demanded to incorporate these new concepts. We propose a web-bused distributed expert system for this purpose. The system consists of four expert systems for design of experiment, acceptance inspection, statistical process control and reliability management corresponding to design quality, incoming-material quality, manufacturing quality and usability quality, respectively, throughout the total product life cycle. Each distributed expert system at the horizontal level in the hierarchy carries out its own quality jobs independently. At the lower level in the hierarchy there is an expert system for measurement analysis to provide reliable data, and at the upper level, an expert system for total quality management to coordinate, integrate and make final decisions. A prototype has been developed and its application is presented.