• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.337-346
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• 2012

Purpose: A Control chart is one of the important statistical process control tools that can improve processes by reducing variability and defects. Methods: In the present study, we propose the local $T^2$ multivariate control chart that can efficiently detect abnormal observations by considering the local pattern of the in-control observations. Results: A simulation study has been conducted to examine the property of the proposed control chart and compare it with existing multivariate control charts. Conclusion: The results demonstrate the usefulness and effectiveness of the proposed control chart.

• IE interfaces
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• v.24 no.2
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• pp.128-138
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• 2011

This research proposes a resource allocation model of Data QC (Quality Control) activities using COQ (Cost of Quality). The model has been developed based on a series of research efforts such as COQ classifications, weight determination of Data QC activities, and an aggregation approach between COQ and Data QC activities. In the first stage of this research, COQ was divided into the four typical classifications (prevention costs, appraisal costs, internal failure costs and external failure costs) through the opinions from five professionals in Data QC. In the second stage, the weights of Data QC activities were elicited from the field professionals. An aggregation model between COQ and Data QC activities has been then proposed to help the practitioners make a resource allocation strategy. DEA (Data Envelopment Analysis) was utilized for locating efficient decision points. The proposed resource allocation model has been validated using the case of Korea national defense information system. This research is unique in that it applies the concept of COQ to the data management for the first time and that it demonstrates a possible contribution to a real world case for budget allocation of national defense information.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.1-10
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• 2016

This paper considers WiMedia UWB network based wireless ship area network (WSAN) so as to support high-quality multimedia video data services and important shipboard control data. In this paper, prioritized contention access (PCA) and distributed reservation protocol (DRP) based on WiMedia UWB (ECMA-368) MAC protocols are combined and proposed to support mixed high-quality video traffic and shipboard control data traffic applying varying DRP and PCA data periods according to channel condition and link parameter ptimization. It is shown that the proposed dynmaic channel allocation of WiMedia UWB MAC protocol can provide reliable mixed video and shipboard control data traffic as well.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.524-528
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• 1996

Quality information is known to have the characteristic of continuous distribution in many manufacturing processes. It is difficult to describe the process condition by classifying the distribution into discrete ranges which is based on the set concept. Fuzzy control chart has been developed for the control of linguistic data but it still utilizes the dichotomous notion of classical set theory. In this paper, the fuzzy sampling method is studied in order to manage the ambiguous data properly and incorporated for generating fuzzy control chart. The method is based on the fuzzy set concept and considered to be appropriate for the realization of a complete fuzzy control chart. The fuzzy control chart was compared with the conventional generalized p-chart in the sensitivity for quality distribution and robustiness against the noise. The fuzzy control chart with the fuzzy sampling method showed better characteristics.

• Corrosion Science and Technology
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• v.23 no.2
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• pp.131-138
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• 2024

This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.313-318
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• 2006

Many control charting methods for both i.i.d and autocorrelated data can be viewed as charting the output of a linear filter applied to the process data. We propose a generalization of this concept, in which the filter parameters are optimally selected to minimize the out-of-control ARL while constraining the in-control ARL to some desired value. A number of interesting characteristics of the optimal fitters are discussed.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.3
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• pp.243-249
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• 2013

Objectives: This study assessed the status of domestic industrial hygiene laboratories using data from on-site investigation for revision of quality control systems in 2012-2013. Methods: The target laboratories were 60 industrial hygiene laboratories chosen by random selection and nationwide distribution which had participated in on-site investigations for revision of quality control systems from March 2012 to August 2013. The investigation was performed on-site following standard quality control procedures. The score between each group was compared using Mann-Whitney and Kruskal-Wallis tests, and the correlation between analytical career, sex, academic major of analyst and score of analytical performance was expressed as Spearman's rank correlation coefficient. Results: The assessment revealed that the items to be improved, in sequence, were effort at staff training (score 65.5), ability to calculate data (score 73.4), establishment of internal quality control guidelines (score 75.7), laboratory facilities (score 77.1), degree of understanding and skill at gas chromatography (score 77.1). Analysis performance showed a positive correlation with career of analyst (r=0.56, p<0.01). Conclusions: The practice of on-site investigation for quality control systems showed the current status of industrial hygiene laboratories in the first trial. There were many laboratories which needed improvement and development of analytical systems. This assessment can provide information for the systematic operation and improvement of facilities at each laboratory. Further practice of this investigation will lead to a proficiency testing and accreditation system for autonomous quality control as is the practice in many countries, rather than mandatory practice by legal regulation.

• The Korean Journal of Emergency Medical Services
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• v.9 no.1
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• pp.101-109
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• 2005

The purpose of this study which was done by 250 Prehospital Care Reports(PCRs) survey of some squads in Seoul Metropolitan Fire & Disaster Management Department was to improve prehospital emergency care by means of quality management. The data were collected in 3 squads from Jun. 21 to Jul. 18, 2004 and analyzed by using SPSS Win 12.0 Version. The conclusions from this study were summarized as follows. The mean time of Event to treatment interval was $4.6{\pm}4.3$ minutes and 49.2% arrived at patient within 4 minutes. Platinum minute was observed 61.1% of verbal response, 73.3% of painful response, 77.8% of unresponsive. The great majority of patients couldn't receive advanced life support on account of limited scope of practice and strict direct medical control in the Emergency Medical Services Act. Data from quality improvement activity will be useful to expand indirect medical control which is able to activate prehospital care. To utilize PCR for quality improvement. It has to have data elements, run data, patient data, check boxes, narrative including US DOT's minimum data set.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.823-833
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• 2005

This paper deals the TFT-LCD process and quality, process control problems of the process. For improvement of the process quality and yield, we apply a data mining technique to the LCD industry. And some unique quality features of the LCD process are also described. We describe some preceding researches first and relate to the TFT-LCD process and the problems of data mining in the process. Also we tried to observe the problems which need to solve first and the features from description below hazard must be considered a quality mining in LCD industry.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.161-174
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• 2014

The methodology report '2006 IPCC Guidelines for National Greenhouse Gas Inventories' shows higher tier method can be a good practice, which uses country-specific or plant-specific data when calculating greenhouse gas emissions by country. We review the methodology report to present principles of using plant-level data and also examine examples of using plant-level data in chemical and metal industry in 20 countries for the purpose of quality improvement of national greenhouse gas inventories. We propose that Korea consider utilizing plant-level data, as reported according to 'Greenhouse gas and Energy Target Management Scheme', in the following order as a preference. First, the data can be utilized for quality control of Korea's own parameters, when Tier 2 method is adopted and bottom-up approach is not applicable. Second, both plant-level data and IPCC default data can be used together, combining Tier 1 method with Tier 3 method. Third, we can also use acquired plant-level data and country specific parameters, combining Tier 2 method with Tier 3 method. Fourth, if the plant-level data involves all categories of emissions and the data is proven to be representative, we can apply Tier 3 method. In this case, we still need to examine the data to check its reliability by a consistent framework, including appropriate quality control.