• 한국경영과학회지
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• 제34권1호
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• pp.11-28
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• 2009

Intelligent investment in setup cost reduction and process reliability improvement is crucial to an emerging integrated lean six sigma practice today. This study examines a cost-minimizing problem of jointly determining production lot size, setup cost reduction, and process reliability improvement decisions for a manufacturer with an imperfect production process. We develop models for previously untapped discrete shipping in a supply chain context as well as continuous shipping and solve them optimally using differential calculus and nonlinear programming. We also conduct analytic and numerical sensitivity analyses to provide various important managerial insights into practices.

• International Journal of Quality Innovation
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• 제2권2호
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• pp.24-33
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• 2001

As we know, the quality of processes is technically depicted by variation, a product or process with the best quality must naturally require the variation as less as possible. The variation is usually reduced with many ways, say, by adjusting parameters settings under robust design with many turns expensive experiments. So ones are trying to reach the robustness by detecting cheap and simple methods. In this paper, a both practical and simple technique for quality improvement, namely reducing the variation, by data classification is studied. First, all possible system factors are included, which may dominate the variation law. And then we make use of the past observations and their classification as well as boxplot charts to find out the internal rule between the variation and the system factor. Next, adjust the location of the system factor according to the rule so that the variation could, to some extent, be lessened. Finally, two typical quality improvement cases based on data classification are presented.

• 품질경영학회지
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• 제32권4호
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• pp.184-195
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• 2004

Current companies 집중 on how to operate and select projects to achieve the best result. 6sigma projects are chosen in the best suitable concept, which are solved by the 6Sigma experts according to the priority. And every project has to be launched not the view of individual management factors but the total factors, Big Y. Therefore, a process needs to be treated to connect the vital few factors in various processes to improve the yield, which is the main performance criteria in a manufacturing industry This report is to make the total optimization through the Vital-Few mapping between quality characteristics and process factors in a manufacturing line. Accordingly, it means to secure lower variance by making the CTP(Critical To Process) optimization and finally to improve the yield.

• 산업경영시스템학회지
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• 제18권36호
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• pp.121-131
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• 1995

The purpose of a business's existence is to make profit. The objective of business can be attained through the most profitable activities such as the improvement of productivity, quality and the reduction of the manufacturing cost. In order to produce the goods with above said goal, it can be achieved by inducing and improving the manufacturing process. In this viewpoint, We'd like to develope an algorithm for improving productivity, quality and cutting the manufacturing cost under the limitation of the resources. This paper showed a practical method which gradually improves three factors [productivity, quality and cost-down] by calculating the effective value of single and multi process mutually.

• Journal of Information Technology Applications and Management
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• 제9권3호
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• pp.113-127
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• 2002

The effort for software process improvement is lately surging its interest though it does not satisfy both developer and receiver In terms of low productivity, quality, delay and increasing cost. According to current research, software process improvement contributes to improvement of productivity, its Duality, reduction of development time and cost, and the prediction of the time limit for delivery, which means software process improvement affects competitive advantage among developers. The latest research is whether the investment for information technology substantially had effect on improvement of productivity. That is, software process improvement and maturity of software industries has influence upon economic efficiency and as a result, it plays an important role in whole industries. This research is that how does software process improvement using CMM (Capability Maturity Model) and SPICE (Software Process Improvement and Capability dEtermination) have a effect on factors of software engineering, and how does it have influence upon competitive advantage among SI firms. For this research, reusability, customizability, participation, and review & inspection are set to independent variable and process flexibility and process predictability are set to mediate Variable. Finally, competitive advantage among SI firms Is set to dependent variable. The targets for survey are laborers who work for SI firms. The result of this research is as follows: 1 ) Reusability, Customizability and participation is not rejected but review and Inspection is rejected in process flexibility which has significant level 0.05. 2) Reusability, Customizability and participation is not rejected but review and inspection Is rejected in process predictability which has significant level 0.05. 3) Process flexibility is not rejected and process predictability Is rejected in the competitive advantage of 51 industries which has significant level 0.05

• 품질경영학회지
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• 제50권3호
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• pp.373-386
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• 2022

Purpose: This study proposes the application of Six Sigma management innovation method for more systematically enhanced execution of Quality by Design (QbD) activities. QbD requires a deeper understanding of the product and process at the design and development stage of the drug, and it is very important to ensure that no fault is fundamentally generated through thorough process control. Methods: Analyzing the background and specific procedures of quality improvement based on the drug design basis, and analyzing the key contents of each step, we have differentated and common points from the 6 Sigma methodology. We propose a new model of Six Sigma management innovation method suitable for pharmaceutical industry. Results: Regulatory agencies are demanding results from statistical analysis as a scientific basis in developing medicines to treat human life through quality improvement activities based on drug design. By utilizing the education system to improve the statistical analysis capacity in the Six Sigma activities and operating the 6 Sigma Belt system in conjunction, it helped systematically strengthen the execution power of quality improvement activities based on pharmaceutical design based on the members of the pharmaceutical industry. Conclusion: By using QbD Six Sigma, which combines quality enhancement based on pharmaceutical design basis and Six Sigma methodology suitable for pharmaceutical industry, it is possible to obtain satisfactory results both by pharmaceutical companies and regulators by using appropriate statistical analysis methods for preparing scientific evidence data required by regulatory.

• International journal of advanced smart convergence
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• 제11권4호
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• pp.273-278
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• 2022

Uncertainty is increasing around the world due to COVID-19 and Ukraine crisis. In this situation, each company is making countless efforts to survive. In Korea, smart factory projects targeting small and medium-sized businesses with difficulties have been continuously promoted. As for the smart factory business that has been promoted so far, the base expansion of the smart factory is also steadily increasing as the number of companies carrying out the project is increasing. It was also found that it contributed to productivity improvement and quality improvement. Despite these positive aspects, difficulties and operational problems are also appearing in the process of promoting smart factories. In this study, we investigated and analyzed operational problems and difficulties in the process of promoting smart factories. In addition, improvement plans for problems were presented according to the contents of this analysis, and improvement plans were presented by classifying them into introduction and supply companies, considering that the smart factory business is formed in the form of a consortium between introduction and supply companies.

• 인터넷정보학회논문지
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• 제8권5호
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• pp.151-160
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• 2007

다양한 분석 정보를 추출하여 저장하는 데이터웨어하우스는 기업의 마케팅 및 의사결정 지원을 위해 사용된다. 그러나 데이터웨어하우스는 분산되어 저장된 대규모의 데이터를 통합하기 때문에 처리 시간과 비용이 증가하며 오류 발생의 위험이 높다. 따라서 개발생산성의 향상 및 비용을 절감하기 위해 본 연구에서는 생산성, 프로세스 품질, 데이터 품질의 영역에서 프로세스 측정지표를 설계하여 제안한다. 또한 측정 지표를 이용하여 프로세스를 평가하고 평가결과를 분석하여 개발생산성의 향상과 프로세스가 개선됨을 보인다.

• 한국경영과학회지
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• 제12권1호
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• pp.111-111
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• 1987

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• 경영과학
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• 제12권1호
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• pp.111-124
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• 1995

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.