• 한국통계학회:학술대회논문집
• /
• 한국통계학회 2005년도 춘계 학술발표회 논문집
• /
• pp.191-196
• /
• 2005

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a MLE of the process change point when control charts with the fixed sampling rate (FSR) scheme or the variable sampling rate (VSR) scheme monitor a process to detect changes in the process mean and/or variance of a normal quality variable.

• Journal of the Korean Statistical Society
• /
• 제14권2호
• /
• pp.76-86
• /
• 1985

Shewhart X-chart, which is most widely used in practice, is shown to be inappropriate for the cases where the process distribution is one-sided asymmetrical, and thus some nonparametric Shewhart type charts are developed instead. These schemes may be applied usefully when there is not enough information in determining the process distribution. The average run lengths are obtained to compare the efficiency of control charts for various shifts of the location parameter and for some typical one-sided asymmetrical distributions.

• 산업경영시스템학회지
• /
• 제16권28호
• /
• pp.173-180
• /
• 1993

This paper is to propose the procedure for improving the level of product specification in statistical process control using loss function. The procedure proposed in this paper is extended to the Taguchi's Quality engineering concept This procedure will be useful in establishing product specification. This paper is aimed to provide customer satisfaction for consumer and quality management for producer.

• 산업경영시스템학회지
• /
• 제39권3호
• /
• pp.10-17
• /
• 2016

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally ${\bar{x}}-R$ control chart or ${\bar{x}}-s$ control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

• 한국수학교육학회지시리즈A:수학교육
• /
• 제50권2호
• /
• pp.185-212
• /
• 2011

The purpose of this study is to analyze whether spreadsheet-used instruction can improve statistical thinking ability and attitude and also to identify what characteristics of statistical thinking is constructed. For this study, a subject of 2 classes were randomly selected among the 12 classes of the 11th grader in D high school and designated one class as the experimental group and the other class as the control group. Eight hours of the spread sheet-used instruction and the traditional textbook-oriented instruction had been carried out in each class. The research findings are as follows. First, the spread sheet-used instruction is shown to be more effective in enhancing statistical thinking than the traditional textbook-oriented instruction. Second, the spread sheet-used instruction is shown to be more effective in improving statistical attitude than the traditional textbook-oriented instruction. Third, students have shown the various characteristics of statistical thinking in the data descriptive process, data arrange-summary process, data representing process, and data analying process through the spread sheet-used instructions. Hence, the spread sheet-used instruction is recommended in teaching statistics.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
• /
• pp.740-745
• /
• 1988

New design methods for constructing nonlinear adaptive control system are considered. The proposed adaptive controllers are applicable to the case where the degree of the controlled process is unknown. It is shown that the degree of the controller is determined independently of the degree of the process. Several types of nonlinear functions are introduced to deal with uncertainties of the degree of the process. Finally, some simulation results show the effectiveness and simplicity of the proposed methods.

• Journal of the Korean Data and Information Science Society
• /
• 제19권4호
• /
• pp.1191-1200
• /
• 2008

Recently classroom monitoring is becoming important since the lecture is being held in the classroom and academic institutions are interested in the quality assurance. Some institutions have adopted ISO 9000 systems and constructed monitoring system through measurement, analysis and improvement. In this study quality assurance problems in academic institutions and the requirements of ISO 9001:2000 will be briefly discussed. Next we will investigate how to monitor the lecture in the classroom(in-class) using statistical process control techniques such as control charts. Then case study will be given to illustrate the technique to use appropriate statistics. Finally how to monitor the learning process during in-class and after-class will be proposed.

• 산업경영시스템학회지
• /
• 제34권4호
• /
• pp.57-65
• /
• 2011

Monitoring auto correlated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment through sensor rather than resultant output status of the processes. Equipment's sensor data show various forms of correlation features. Among them, considerable amount of sensor data, statistically autocorrelated, is well represented by Box-Jenkins autoregressive moving average (ARMA) model. In this paper, we present a design method of statistical process control (SPC) used for monitoring processes represented by the ARMA model. The proposed method shows benefits in the power of detecting process changes, and considers robustness to ARMA modeling errors simultaneously. We prove benefits through Monte carlo simulation-based investigations.

• Communications for Statistical Applications and Methods
• /
• 제21권1호
• /
• pp.69-80
• /
• 2014

This paper considers the problem of monitoring the mean of a normally distributed process variable when the objective is to effectively detect both a sustained shift and a linear drift. The design and application of a generalized likelihood ratio (GLR) chart for simultaneously monitoring a sustained shift and a linear drift are evaluated. The GLR chart has the advantage that when we design this chart, we do not need to specify the size of the parameter change. The performance of the GLR chart is compared with that of other control charts, such as the standard cumulative sum (CUSUM) charts and the cumulative score (CUSCORE) charts. And we compare the proposed GLR chart with the GLR charts designed for monitoring only a sustained shift and for monitoring only a linear drift. Finally, we also compare the proposed GLR chart with the chart combinations. We show that the proposed GLR chart has better overall performance for a wide range of shift sizes and drift rates relative to other control charts, when a special cause produces a sustained shift and/or a linear drift in the process mean.

• 산업경영시스템학회지
• /
• 제30권2호
• /
• pp.99-105
• /
• 2007

According to the automated manufacturing processes followed by the development of computer manufacturing technologies, products or quality characteristics produced on the processes have measured and recorded automatically. Much amount of data daily produced on the processes may not be efficiently analyzed by current statistical methodologies (i.e., statistical quality control and statistical process control methodologies) because of the dimensionality associated with many input and response variables. Although a number of statistical methods to handle this situation, there is room for improvement. In order to overcome this limitation, we integrated data mining and robust design approach in this research. We find efficiently the significant input variables that connected with the interesting response variables by using the data mining technique. And we find the optimum operating condition of process by using RSM and robust design approach.