• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.111-116
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• 2005

This paper considers the problem of optimally choosing the sub-process means of a mixture production process where two important ingredients are mixed. The quantity of each ingredient is controlled through each corresponding sub-process. The values of the sub-process mean directly affect the defective rate, production, scrap and reprocessing costs for the mixture production process. After inspecting every incoming item, each conforming item is sold in a regular market for a fixed price and any nonconforming item is scraped. A model is constructed on the basis of the selling price, production, inspection, and scrap and reprocessing costs. The goal is to determine the optimum sub-process mean values based on maximizing expected profit function relating selling price and cost components. A method of finding the optimum sub-process means is presented when the quantities of the two ingredients are assumed to be normally distributed with known variances. A numerical example is given and numerical studies are performed.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.425-429
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• 2004

Process adjustment Is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.288-296
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• 2008

Software in defense domain requires high quality since defense specific characteristics. To assure high quality products, development and testing activities based on well defined process must be performed. If those activities cannot support software acquisition process, the quality of acquired software product is low and combat power decreases. In this paper, we propose MND-TMM(Ministry of National Defense-Testing Maturity Model), which can help enhance software quality through testing process improvements. This paper also introduces the contents of MND-TMM architecture. MND-TMM is constituted to reflect the characteristics of defense software, development process, and testing process so as to solve the problems associated with software testing. MND-TMM is comprised of 5 maturity levels and 4 categories which have number of related TPA(Testing Process Area)s. It is expected that MND-TMM can help assess testing maturity of defense software organizations and provides guidelines to improve software testing process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.95-100
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• 2020

Machines and facilities are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. The representative type of the degeneration is wear of tool or machine. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore a periodic preventive resetting the process is necessary. The total cost consists of three items: adjustment cost (or replacement cost), non-conforming cost due to product out of upper or lower limit specification, and quality loss cost due to difference from the process target value and the product characteristic value among the conforming products. In this case, the problem of determining the adjustment period or wear limit that minimizes the total cost is called the 'process mean shift' problem. It is assumed that both specifications are set and the wear level can be observed directly. In this study, we propose a new model integrating the quality loss cost, process variance, and production volume, which has been conducted in different fields in previous studies. In particular, for the change in production volume according to the increasing in wear level, we propose a generalized production quantity function g(w). This function can be applied to most processes and we fitted the g(w) to the model. The objective equation of this model is the total cost per unit wear, and the determining variables are the wear limit and initial process setting position that minimize the objective equation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.45-50
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• 2021

Machines and facilities are physically or chemically degenerated by continuous usage. The representative type of the degeneration is the wearing of tools, which results in the process mean shift. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore, a preventive maintenance is necessary at some point. The problem of determining the maintenance period (or wear limit) which minimizes the total cost is called the 'process mean shift problem'. The total cost includes three items: maintenance cost (or adjustment cost), non-conforming cost due to the non-conforming products, and quality loss cost due to the difference between the process target value and the product characteristic value among the conforming products. In this study, we set the production volume as a decreasing function rather than a constant. Also we treat the process variance as a function to the increasing wear rather than a constant. To the quality loss function, we adopted the Cpm+, which is the left and right asymmetric process capability index based on the process target value. These can more reflect the production site. In this study, we presented a more extensive maintenance model compared to previous studies, by integrating the items mentioned above. The objective equation of this model is the total cost per unit wear. The determining variables are the wear limit and the initial process setting position that minimize the objective equation.

• Spatial Information Research
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• v.17 no.2
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• pp.231-241
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• 2009

Recently, The importance of a quality control for implementing 3D geospatial database has being emphasized to build a 21st century knowledge society and an ubiquitous land. The improvement of 3D geospatial database quality control through establishing an integrated quality control makes data suppliers update data efficiently and users get high quality data. The purpose of this study was to derive the improvement plan of 3D geospatial database quality control through the analyses of the existing 3D geospatial database quality control and case studies. The results of this study are as follows. Firstly, we defined the concept of 3D geospatial database quality control. Secondly, we set the boundary, factors and process of 3D geospatial database quality control through classifying it in detail. Lastly, we drew improvement contents such as the quality control checklist by implementation process according to the improvement plan of 3D geospatial database implementation.

• Korean Journal of Construction Engineering and Management
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• v.1 no.1 s.1
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• pp.72-79
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• 2000

Design quality in constructed project is a primary consideration to achieve overall project objectives. It is not easy to evaluate the design quality because various factors are involved in the design process. This paper presents a new approach to improve the evaluation process of design quality In the construction project The evaluation model is developed to satisfy the requirement for implementing the ISO 9000 Quality Assurance Standards in the design process. It is assumed that design changes are resulted from the poor management of design quality. The model relates design changes to design quality management items. It assigns weight ratio to each design quality item to evaluate quantitatively Design Quality Index (DQI) is calculated to assess design quality based on the Objectives Matrix. A case study is performed to illustrate the practical implementation of the design quality evaluation.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.51-71
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• 2023

This study analyzed the government data quality management model, big data quality management model, and data lifecycle model for research data management, and analyzed the components common to each data quality management model. Those data quality management models are designed and proposed according to the lifecycle or based on the PDCA model according to the characteristics of target data, which is the object that performs quality management. And commonly, the components of planning, collection and construction, operation and utilization, and preservation and disposal are included. Based on this, the study proposed a process model for research data quality management, in particular, the research data quality management to be performed in a series of processes from collecting to servicing on a research data platform that provides services using research data as target data was discussed in the stages of planning, construction and operation, and utilization. This study has significance in providing knowledge based for research data quality management implementation methods.

• Journal of Korean Society for Quality Management
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• v.38 no.4
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• pp.540-548
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• 2010

We consider the problem of selecting the most profitable initial process mean and length of production cycle for manufacturing processes subject to a constant linear trend during the same cycle that varies after resetting the processes. Assuming that the quality characteristic of interest is normally distributed, the optimum initial process mean and the length of production cycle are jointly obtained by minimizing the expected loss per unit time. We assume that the quality loss function due to the deviation from the target value is quadratic and resetting loss is constant. We consider both cases of symmetric and asymmetric quality loss function. An illustrative example is given and sensitivity analysis performed.

• Korean Journal of Health Education and Promotion
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• v.20 no.1
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• pp.1-17
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• 2003

This study purports to assess the process quality of health promotion programs at public health centers. The sample used in this study consisted of 242 public health centers in South Korea. Data was collected with self-administered questionnaires between September. 3rd to September. 23rd in 2002. The 95 returned questionnaires were analyzed by SPSS 11.0 version. The major findings are as follows; There is a need to improve (1) a procedure for reviewing and analyzing strategic planning, (2) the quality of the staff in charge of program management, (3) the function of planning and training for monitoring and evaluation, (4) the ability of program managers in advising and consulting with clients, and (5) a procedure for organizing resources and information. In conclusion, in order to improve the process quality of health promotion programs at public health centers, integrated support from various institutions such as public health centers, community, regional and national health authorities and administrative departments is required.