• 한국산업정보학회논문지
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• 제8권1호
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• pp.1-8
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• 2003

There are many statistical evaluation methods, A more technical Perspective is needed in estimating the effect of the Manufacturing Process for improving the Productivity, Process network analysis is a technique which has the potentiality for a wire use to improve the manufacturing process which other techniques can't be used to analyze effectively. The concept of six sigma plan was developed and pursued by Motorola to improve the process control. The goals of six sigma plan are established on the foundation of customer satisfaction such as Quality, Cost Delivery and Service This paper presents how to improve the manufacturing process by statistical process control for the evaluation of six sigma level.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.509-520
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• 2005

Data fusion is defined as the process of combining data and information from different sources for the effectiveness of the usage of useful information contents. In this paper, we propose a data fusion algorithm using k-means clustering method for data enrichment to improve data quality in knowledge discovery in database(KDD) process. An empirical study was conducted to compare the proposed data fusion technique with the existing techniques and shows that the newly proposed clustering data fusion technique has low MSE in continuous fusion variables.

• 한국수학교육학회지시리즈A:수학교육
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• 제60권3호
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• pp.363-386
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• 2021

통계를 의미 있게 학습하기 위해서는 실제 데이터로 통계적 문제해결을 경험할 수 있는 기회를 제공해야 한다. 특히 문제 설정 단계에서의 탐구 질문은 학생들이 통계적 문제해결 과정의 시작부터 결론까지 성공적으로 안내하는 데에 중요하다. 이에 본 연구는 문제 설정 단계에서 예비 수학교사들의 탐구 질문에 대해 혼합연구방법을 실시하였다. 그 결과 일부 예비 수학교사들은 통계적 질문을 분류하는 과정에서 질문의 의미나 변수가 명확하지 않거나 통계 지식에 대한 오개념으로 인하여 통계적으로 해결할 수 없는 질문을 분류하였다. 또한 예비 수학교사들의 50%만이 통계적 문제해결에 적합한 6가지 조건을 모두 충족시켰으며, 나머지 50%는 일부 조건만 충족시켰다. 따라서 이러한 결과는 예비 수학교사들에게 교사 교육을 통해 통계적 문제해결 과정을 경험할 수 있는 기회를 제공해야하며, 그 중 문제 설정 단계는 매우 중요하므로 문제 설정 단계도 일련의 세분화된 과정이 필요하다는 점을 제안할 수 있다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제11권3호
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• 산업경영시스템학회지
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• 제26권1호
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• pp.7-16
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• 2003

At present, company has to produce a product that consumer like with a competitive price, a good quality, and a fitting time to supply. Process control and quality control are very important to supply with a product uniformly and inexpensively. Process control is given much weight in the quality control in manufacturing system. Statistical process controls(SPC) that are used in process generally have major impact on manufacturing, product design activities, and process development potentially. Control charts in statistical process control method can be interpreted the data from quality characteristics in production process and discriminated between chance variation and assignable variation in process. In addition, control chart can be used to monitor the process output and detect when changes in the inputs are required to bring the process back to an in-control state. The models that relate the influential inputs to process outputs help determine the nature and magnitude of the adjustments required. In this paper, the characteristic of product quality is monitored by control chart during the machining process and construction of quality control cycle is considered to divide into two types in this case that different assignable causes lead to shifts having different magnitudes. Then we are intended to find a process shift magnitude which has economical quality cost policy and are considered to quality cost functions to find a process shift magnitude. Those costs are categorized into the well-known categories of prevention, appraisal, and internal failure and external failure. This paper ends with numerical examples that demonstrate the usefulness of the model.

• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.307-324
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• 1993

The limiting distribution of the excess over the boundary is determined for the autoregressive process.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.141-146
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• 2007

In this paper, we consider a Box-Cox transformed threshold GARCH(1,1) process and find a sufficient condition under which the process is geometrically ergodic and has the ${\beta}$-mixing property with an exponential decay rate.

• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.94-100
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• 1995

Vector autoregressive process disturbed by measurement error is a vector autoregressive process with nonlineat parametric restrictions on the parameter. A Newton-Raphson procedure for estimating the parameter which take advantage of the information contained in the restrictions is proposed.

• 대한안전경영과학회지
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• 제15권1호
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• pp.283-292
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• 2013

This paper aims to propose a new steps of hypothesis testing using analysis process and improvement process in the six sigma DMAIC. The six sigma implementation models proposed in this paper consist of six steps. The first step is to establish a research hypothesis by specification directionality and FBP(Falsibility By Popper). The second step is to translate the research hypothesis such as RHAT(Research Hypothesis Absent Type) and RHPT(Research Hypothesis Present Type) into statistical hypothesis such as $H_0$(Null Hypothesis) and $H_1$(Alternative Hypothesis). The third step is to implement statistical hypothesis testing by PBC(Proof By Contradiction) and proper sample size. The fourth step is to interpret the result of statistical hypothesis test. The fifth step is to establish the best conditions of product and process conditions by experimental optimization and interval estimation. The sixth step is to draw a conclusion by considering practical significance and statistical significance. Important for both quality practitioners and academicians, case analysis on six sigma projects with implementation guidelines are provided.

• 대한수학교육학회지:학교수학
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• 제19권4호
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• pp.731-749
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• 2017

본 연구의 목적은 현재 우리가 사용하고 있는 수학교과서가 학생들의 통계적 소양을 함양시킬 수 있도록 구성되어 있는지를 알아보는데 있다. 이를 위하여 맥락의 4가지 유형과 통계적 문제해결 과정을 토대로 2009 개정 수학과 교육과정에 따른 9종의 중학교 3학년 수학교과서의 통계단원의 문항을 분석하였다. 분석결과 맥락의 4가지 유형 중에 개인적 맥락의 유형에 해당하는 문항이 67%로 가장 많은 비중을 차지하였고, 통계적 문제해결 과정 중에서는 자료 분석 과정이 72.8%로 가장 많은 것으로 나타났다. 본 연구의 결과에 의하면 다양한 맥락을 활용한 문항을 통해 통계의 필요성을 인식하고, 자료를 수집하는 과정부터 제시된 자료에서 합리적인 결론을 추측해보는 활동을 통하여 통계적 소양을 함양시킬 수 있는 문항들이 더 포함되어야 함을 알 수 있었다.