This paper uses a data mining methodologies to improve and predict cause of defect process variables in manufacturing process. Traditional statistical process control (SPC) techniques of control charting are not applicable in many process industries because it is difficult to analyze the cause of many process variables. The paper suggests that data mining methodologies useful when sequence rule, SVM (classification) methods are find out cause of defect process variables and SVM (prediction) methods used to predict process variables in manufacturing process. Therefore, it is allowing improved control in manufacturing process.

Recently we developed the eZ Six Sigma software for education of Hanyang University in 2004. This eZ Six Sigma software focused on educational parts. In this paper, we present introduction and Contents of this Software. This software will be helpful to improvement of Six Sigma educational environment.

Being in an internet era, the rapid transmission of 3D mesh models is getting more Important and efforts toward the compression of various aspects of mesh models have been provided Even though a mesh model usually consists of coor-dinates of vertices and

효과적으로 공정을 관리하기위하여 제품의 품질특성치에 영향을 주는 데이터를 수집하고 공정을 해석하여한다. 이를 위해서 데이터 마이닝(Data Mining)이 많이 수행되어지고 있다. 본 연구에서는 공정으로부터 수집된 대량의 정보 데이터를 신경망(Neural Network)기법을 통하여 공정의 불량률을 예측하고 불량률이 높게 나타난 데이터를 통해 연관규칙(Association Rule)을 적용하여 불량에 영향을 주는 공정의 패턴을 파악 공정을 개선하고자 한다.

환경이란 우리주변을 둘러싸고 있는 물리적인 모든 것들을 뜻하는 것으로 주로 대기, 수질, 토양을 일컫는 말이다. 본 연구에서는 이러한 환경이라는 범위 안에서 가장 이슈가 되고 있는 오염 배출 물질 문제에 관한 것으로, 그 중 오염 배출 물질의 모니터링 방법에 관해서 다루고 있다. 환경 분야에서도 환경오염 배출 물질에 대한 비정상적인 변화나 시스템적인 패턴 등을 감지하는 목적으로 일반적으로 공정관리에서 주로 쓰이는 통계적 공정관리 기법 중 하나인 관리도를 사용하기 시작했다. 본 연구에서도 이러한 통계적 공정관리 기법을 환경관리 분야에 적용하여 공정관리에서 쓰이는 공정능력과 관리도의 개념을 환경문제에 적용시켜 오염 배출 물질에 대한 환경 관리 능력을 평가, 모니터링 하는 새로운 평가지표의 관리도를 제안, 설계하고자 한다.

The coefficient of variation(CV) which is a relatively dimensionless measure of variability is widely used to describe the variation of sample data. However, the properties of CV distribution are little available and few research has been done on estimati

In statistical process control applications, variable sample size (VSS) chart is often used to detect the assignable cause quickly. However, it is usually assumed that only one assignable cause results in the out-of-control in the process. In this paper,

Data mining technique is the exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. This paper uses a data mining technique for the prediction of defect types in manuf

기술의 발달과 고객의 다양한 요구에 의해 제품은 점점 다양해지고 또한 복잡해지고 있다. 이에 따라 제품에 대한 여러 가지 변수를 동시에 고려해야 한다. 따라서 각 제조불량에 대해 그에 대응하는 Demerit를 설정하여 관리하는 Demerit관리도가 고안되었다. 본 연구는 불량이나 결점이 여러 가지 형태에 의해 발생되는 공정에 대해 기존의 Demerit approach를 확률적으로 접근 및 해석함으로써 이상신호가 발생하였을 경우 공정의 이상원인을 빨리 찾을 수 있도록 이상신호에 대한 쉽고 정확한 해석방법을 제시하고자 한다.

제조 기업들은 공정 내에 불량을 파악하고 품질 특성치를 찾아내기 위해서 대용량의 샘플 데이터를 수집하며 분석하고 있다. 이렇게 수집되어진 데이터를 분석하기 위하여 데이터마이닝 기법이 많이 이용되어지고 있다. 본 연구에서는 제조 공정내의 불량 요인의 데이터를 수집하고 수집된 데이터를 데이터마이닝 기법 중 연관규칙을 이용하여 공정 내 불량간의 연관관계를 파악하고 공정 불량요인을 효과적으로 분석함으로서 제조 공정 내에 불량항목과 공정 간의 변화패턴 관계를 알아보기 위함이다.

Being in an internet era, the rapid transmission of 3D mesh models is getting more important and efforts toward the compression of various aspects of mesh models have been provided. Even though a mesh model usually consists of coordinates of vertices and properties such as colors and normals, topology plays the most important part in the compression of other information in the models. Despite the extensive studies on Edgebreaker, the most frequently used and rigorously evaluated topology compressor, the probability distribution of its five op-codes, C, R, E, S, and L, has never been rigorously analyzed yet. In this paper, we present probability distribution of the op-codes which is useful for both the optimization of the compression performance and a priori estimation of compressed file size.

Recently we developed the eZ Six Sigma software for education of Hanyang University in 2004. This eZ Six Sigma software focused on educational parts. In this paper, we present introduction and Contents of this Software. This software will be helpful to improvement of Six Sigma educational environment.

VSS X 관리도는 이상원인에 의한 공정의 변동이 작은 경우에 통계적으로나 경제적으로 효과적인 관리도이다. 본 연구에서는 두 가지 이상원인이 공정의 평균에 복합적으로 영향을 끼치는 경우 VSS X 관리도의 최적 샘플 크기 결정을 위한 경제적 모형을 제시한다.

CUSUM control charts are widely used in process with small shifts since they have reasonable detection capability for small shifts. CUSUM control charts, however, are less effective in detection for recurring cycles or frequent small shifts in process. With Shewhart control charts, we have applied the variety of run rules to check the stability of process in addition to the situations that some points fall outside the control limits. In this paper, we propose the Z-CUSUM control chart.

Data mining technique is the exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. This paper uses a data mining technique for the prediction of defect types in manufacturing process. The purpose of this paper is to model the recognition of defect type patterns and prediction of each defect type before it occurs in manufacturing process. The proposed model consists of data handling, defect type analysis, and defect type prediction stages. The performance measurement shows that it is higher in prediction accuracy than logistic regression model.

The coefficient of variation(CV) which is a relatively dimensionless measure of variability is widely used to describe the variation of sample data. But little research is available to its distribution, confidence interval and interpret method etc. In this paper, we give an outline of statistical properties of coefficient of variation and design of control chart based on this statistic. Construction procedures of control chart are presented. The proposed control chart is an efficient method to monitoring a process variation for multiple product processes. Futhermore, the performance is evaluated by average run length(ARL).

In the era of customer satisfaction(CS), managers in the service industry have been using new strategies and a new reinforcement of service quality in order to increase their competitiveness. In this paper, the Service-QFD model is based on SERVQUAL and Quality Function Deployment models. The service quality in each stage of service delivery process is measured by SERVQUAL model and the relationship is represented by the QFD model. We propose the effective model that is consistent with preference of users considering of weighting scale, which seriously affects technical importance rating.

We developed the basic SPC software named as 100 ？ Quality Renovation Software in 1998 as a government project supported by the Small and Medium Industry Administration and the Korean Standards Association. In 2002, Ministry of Industry and Energy conducted a survey research on the current status of quality management in the domestic industries including manufacturing and service industries. Among about 1000 answered industries, 40.6% has been using this 100？ S/W for their quality improvement activities. In this paper, we present our ways to help small and medium sized industries improve quality by our user-friendly SPC software.