Companies strive for quality improvement and use process data obtained through measurement process to monitor and control the process. Measurement data contain variation due to error of operator and instrument. The total variation is sum of product variation and measurement variation. Gage R&R is for repeatability and reproducibility of measurement system. Gage R&R study is usually conducted to analyze the measurement process. In performing the gage R&R study, several parameters such as the appropriate number of operators (o), sample size of parts (p), and replicate (r) are used. In this paper we propose how to determine the optimal combination of number of operators (o), sample size of parts (p), and replicates (r) considering measurement time and cost by statistical method.

Traditional quality control for manufacturing or service sector is not suitable for the quality control of a project as the project is one-time task constrained by time, cost, and quality. To meet the internal and external customers’ requirements, quality

전통적인 Demerit 관리도는 일반적으로 자동차, 컴퓨터, 핸드폰 등 하나의 복잡한 제품에서 다양한 유형의 결점들이 동시에 발생하는 공정을 모니터링하기 위하여 사용된다. 관리도에서 공정 평균의 작은 변동을 빠르게 감지하기 위한 방법으로 EWMA기법은 매우 효과적이다. 본 연구에서는 EWMA 기법 보다 공정 평균의 작은 변동에 더 좋은 성능을 보이는 GWMA기법과 전통적인 Demerit 관리도(1928)를 결합한 Demerit-GWMA(generally weighted moving average) 관리도를 제안하였으며 그 관리도의 수행도를 평가하였다. 그 수행도 평가 결과, Demerit-GWMA 관리도는 공정 평균의 작은 변동을 감지하는데 classical Demerit 관리도, Demerit-EWMA. 관리도에 비하여 더 민감하다.

Previous researches have focused on the efficiency of project execution and the satisfaction of internal customers in view of the fact that a project is successful if any defects are not found in the short-term performance test of the project final outcom

When the production run is short and process parameters change frequently, it is difficult to monitor the process using traditional control charts. In such a case, the coefficient of variation (CV) is very useful for monitoring the process variability. Th

When the production run is short and process parameters change frequently, it is difficult to monitor the process using traditional control charts. In such a case, the coefficient of variation (CV) is very useful for monitoring the process variability. The CV control chart is an effective tool to control the mean and variability of process simultaneously. The CV control chart, however, is not sensitive at small shifts in the magnitude of CV. The CV-EWMA(exponentially weighted moving average) control chart which was developed recently is effective in detecting a small shifts of CV. Since the CV-EWMA control chart scheme can be viewed as a weighted average of all past and current CV values, it is very sensitive to small change of mean and variability of the process. In this paper, we propose an FIR(Fast initial response) CV-EWMA control chart to improve the sensitivity of a CV-EWMA scheme at process start-up or out-of-control process. Moreover, we suggest the values of design parameters and show the results of the performance study of FIR CV-EWMA control chart by the use of average run length( ). Also, we compared the performance of FIR CV-EWMA control chart with that of the CV-EWMA control chart and we found that the CV-EWMA control chart gives longer in-control ARL and much shorter out-of-control ARL.

Complex products may present more than one type of defects and these defects are not always of equal severity‘ These defects are class ified according to their seriousness and effect on product quality and performance. So, demerit systems are very effecti

This paper proposes the Data Architecture implementation process and the suggestions for automation which will enable the analyzing and measuring of the data structure as well. We verified the standardization of data that proposes a baseline for minimum quality, communications with stakeholder within an information system, minimization of application changes, and the effect of data values on quality improvement. The baseline is tested through the measurement and assessment of the quality indicator of a data structure as well as a quality control process deduced during the implementation.

프로젝트 성공요인의 하나로 프로젝트 관리자는 항상 관심의 대상이 되어왔다. 기업들은 프로젝트 관리자의 양성을 위해 많은 노력을 기울이고 있으나, 프로젝트 관리자의 다각적 측면의 연구가 미흡하며, 실제적으로 능력을 평가하고, 프로젝트의 진행에 적합한 인력인지 선별하기 어려운 실정이다. 본 연구는 IT서비스 프로젝트의 프로젝트 관리자 (Project Manager)가 갖추어야 할 지식과 기술이 무엇인지 확인하고, 역량 평가의 표준이 되는 지표를 통해 프로젝트 관리자의 자격을 검증할 수 있는 도구를 만들고 활용하고자 하는 것이다. 일반적인 프로젝트 관리자의 지식과 기술, IS인력 혹은 IT서비스 전문가의 지식과 기술이 무엇 인지 기존 연구 문헌과 이론적인 내용을 파악하여 프로젝트 관리자에게 필요한 관리지식과 프로 젝트 수행 능력, 개인의 역량과 IT기술적 측면의 역량의 요소를 해당 산업분야의 전문가에게 의뢰하여 핵심 요소를 도출하고, 인사평가방식의 도구를 활용하여 기술과 관리를 통합하는 역량지표를 통해 실제 프로젝트 관리자에게 평가 해 봄으로써 지표의 활용성을 확인해 보았다. 위 연구를 통해 우수한 프로젝트 관리자를 양성하고 발전시켜 IT서비스 프로젝트의 성공 확률을 높일 수 있는 밑바탕이 될 수 있을 것이다.

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring

A success of network integration project depends on how well we are able to provide a network implementation fulfilled with customer's requirements within an established budge. As its environment have become enlarged and distributed, the interested parties will be increased and as its customer's technologies have become generalized through a lot of learning opportunities, the requirements will be increased and its qualities will be better. Therefore, it is getting difficult to satisfy their requirements and maintain its qualities. Effectively managing conditions that are able to have effects on resources and schedule at the early requirement analysis stage due to the requirement changes at the end of the project, we are about to offer a service quality and requirement management that can fulfill with customer's requests.

Complex Products may present more than one type of defects and these defects are not always of equal severity. These defects are classified according to their seriousness and effect on product quality and performance. Demerit systems are very effective sy

The control chart is widely used statistical process control(SPC) tool that searches for assignable cause of variation and detects any change of process. Generally, ？맴詠？ control chart and ？맴詠？ are most frequently used. When the production run is short and

  Ultra-high voltage transformer industry has characteristic of small quantity batch production system by other order processing unlike general mass production systems. In this industry, observance of time deadline is very important in market competitive

  Recently, the control chart is developed for monitoring processes with normal short production runs by the coefficient of variation(CV) characteristic for a normal distribution. This control chart does not work well in non-normal short production runs.

In recent years, advancement of science technology and ubiquitous use of networking have led to a great increase of the need for high speed wireless internet. This has encouraged the existing Wireless Local Area Network(WLAN) system to build a new territory in the information and communication market. It provides with reasonable price and convenience, however, its connectivity, transmission speed and mobility do not meed consumers' expectations. In this paper, the standards for grading quality according to the purposes of the WLAN service, applying the concept of composition cause of the service quality that has already been agreed upon, will be reconstructed. Also, this study will try to measure the achievements of the actual WLAN service quality by utilizing the realized measurement standards.

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.

재(再) 제조란 폐기된 제품을 회수하여 신제품과 같은 품질상태로 회복시키는 과정으로, 제품의 폐기로 인하여 발생하는 경제적 손실뿐만 아니라 폐기물의 증가로 인한 환경오염의 예방에도 도움을 준다. 이러한 재 제조의 목표는 보다 많은 부품들을 재사용하는 것으로 기존의 수리와 제조 개념이 결합된 형태로서 제품의 완전 해체, 세척, 검사, 부품수리 및 조정과 교체, 제품의 재조립 등의 일련의 단계를 거치게 되며 이 과정에서 부품의 신뢰도는 매우 중요한 요소로 작용하게 된다. 따라서 이 논문에서는 크게 다음의 두 가지 내용에 대해서 다루게 된다. 첫째, 시스템의 가용도를 모델링하는 방법으로 잘 알려진 마코프 모델을 이용하여 재 제조 시스템의 가용도 분석을 위한 모델을 제시한다. 둘째, 가용도 분석을 통한 부품의 재사용 빈도와 이용시간 평가 등을 통하여 재 제조 시스템의 성능을 평가하기 위한 척도를 제시한다.

With development of the database, there are too many data on process variables and the manufacturing process for the traditional statistical process control methods to identify the process variables related with assignable causes. Data mining is useful in