• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.47
• /
• pp.211-218
• /
• 1998

In start-up process control applications it may be necessary to limit the sample size to one measurement. A control chart for individual measurements is used whenever it is desirable to examine each individual value from the process immediately. A possible option would be to use an exponential weighted moving(EWM), using modifying statistics with individual measurement, chart for monitoring the process center, and using a moving range (MR) chart for monitoring process variability. In this paper it is shown that there is scheme in using the EWM procedure based on average run length. An expression for the ARL is given in terms of an integral equation, approximated using numerical quadrature. In this case, where it is reasonable to assume normality and negligible autocorrelation in the observations, provide graphs that simplify the design of EWM-MR chart and taking method of exponential smoothing constant(λ) and constant(K) are suggested. The charts suggested above evaluate using the conditional probability.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 1998.11a
• /
• pp.198-207
• /
• 1998

The p chart approximate to the normal distribution has a difficulty to analyze the process condition precisely when the negative LCL is occurred. Furthermore, the probability of Type I error increases compared with using its original binomial distribution. For a long time the p chart has been used as approximated to the normal distribution because of its easy use. However, it becomes rapid and convenient to calculate the binomial distribution through the development of computer and software, so it is strongly suggested to use the binomial distribution determining control limits to reduce the probability of Type I error. In this study, I suggest that the control limits can be designed in use of binomial distribution and they can be utilized without special software by illustrating the certain work for establishing p-chart with the commercial one(EXCEL).

• Journal of Korean Society for Quality Management
• /
• v.27 no.4
• /
• pp.123-142
• /
• 1999

Conventional SPC assumes that observations are independent. Often in industrial practice, however, observations are not independent. A common approach to building control charts for autocorrelated data is to apply conventional SPC to the residuals from a time series model of the process or is to apply conventional SPC to the weighted or unweighted subgroup means. In this paper, we propose a robust CUSUM control scheme for the detection of level change, without model identification or subgrouping of autocorrelated data. The proposed CUSUM chart and other conventional control charts are compared by a Monte Carlo simulation. It is shown that the proposed CUSUM chart is more effective than conventional CUSUM chart when the process is autocorrelated.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2007.04a
• /
• pp.287-296
• /
• 2007

Pearn et al.(2002) supposed the $C_{pp}$ multiple process performance analysis chart. This chart display multiple processes with the process variation and process departure on one single chart. But, this chart can not display the distribution of the process variation and process departure. With bootstrapping method, we can display the distribution of the process variation and process departure on the $C_{pp}$ multiple process performance analysis chart.

• Journal of the Ergonomics Society of Korea
• /
• v.15 no.2
• /
• pp.1-13
• /
• 1996

The purpose of this study is to suggest a brassiere sizing chart for elderly women. 2 control dimensions(under bust girth and cup size) were chosen as 2 axes of brassiere size chart. A loss function was used to determined intervals of under bust girth and cup size of size chart, because the loss function introduces the concept of frequency to size chart for better customer's satisfaction. From the dual distribution table whose intervals had been determined by a loss function. The 15 sizs, which had more than 2% of appearance were suggested for brassiere size chart. The suggested brassiere sizes covered 87.6% of all subjects. Considering that KS brassiere size chart consisting of 32 sizes covers 88.5%, the suggested brassiere size chart would be considered quite feasible. Also it is suggested supply reference measurement chart relevant to brassiere manufacturing for 10 most frequent sizes.

• Communications for Statistical Applications and Methods
• /
• v.29 no.4
• /
• pp.487-498
• /
• 2022

Social network analysis (SNA) techniques have recently been developed to monitor and detect abnormal behaviors in social networks. As a useful tool for process monitoring, control charts are also useful for network monitoring. In this paper, the degree and closeness centrality measures, in which each has global and local perspectives, respectively, are applied to an exponentially weighted moving average (EWMA) chart and a multinomial cumulative sum (CUSUM) chart for monitoring undirected weighted networks. In general, EWMA charts monitor only one variable in a single chart, whereas multinomial CUSUM charts can monitor a categorical variable, in which several variables are transformed through classification rules, in a single chart. To monitor both degree centrality and closeness centrality simultaneously, we categorize them based on the average of each measure and then apply to the multinomial CUSUM chart. In this case, the global and local attributes of the network can be monitored simultaneously with a single chart. We also evaluate the performance of the proposed procedure through a simulation study.

• Journal of the Korea Society of Computer and Information
• /
• v.9 no.4 s.32
• /
• pp.215-220
• /
• 2004

Production management confronted the environment of infinite competition should be prepared to abrupt variations of management environment and have the ability to be changed in short term. It has to be studied, the control method of products that correspond to multi-functionalization and reduced product life which is caused by high-quality and varied customers demands. As a process control method, we most be able not only to control varies characteristic in a control at once but also to detected special values quickly for high-quality. In this paper a control method referred above is presented.

• Communications for Statistical Applications and Methods
• /
• v.22 no.5
• /
• pp.519-530
• /
• 2015

The geometric chart has proven more effective than Shewhart p or np charts to monitor the proportion nonconforming in high-quality processes. Implementing a geometric chart commonly requires the assumption that the in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice in high-quality process where the proportion of nonconforming items is very small. Thus, the error in the parameter estimation increases and may lead to deterioration in the performance of the control chart if a sample size is inadequate. We suggest adjusting the control limits in order to improve the performance when a sample size is insufficient to estimate the parameter. We propose a linear function for the adjustment constant, which is a function of the sample size, the number of nonconforming items in a sample, and the false alarm rate. We also compare the performance of the geometric charts without and with adjustment using the expected value of the average run length (ARL) and the standard deviation of the ARL (SDARL).

• Communications for Statistical Applications and Methods
• /
• v.17 no.3
• /
• pp.357-365
• /
• 2010

This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) noise process that is being adjusted using a minimum mean squared error adjustment. As a SPC procedure, we use a GLR chart for detecting special causes whose effects are the sustained shift or the sustained drift in the process mean, and the sustained shift in the process variance. For the design of the GLR chart, we derive expressions for the control limit which accurately satisfies the given in-control ARL.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.3
• /
• pp.633-644
• /
• 2004

Exponentially Weighted Moving Average(EWMA) control chart for variance-covariance matrix of several quality characteristics based on accumulate-combine approach has proposed. Numerical computations show that multivariate EWMA chart based on accumulate-combine approach is more efficient than corresponding multivariate EWMA chart based on combine-accumulate approach.