• Journal of Korean Society for Quality Management
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• v.45 no.2
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• pp.209-225
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• 2017

Purpose: Since traditional p chart is unable to deal with the variation of attribute data, this paper proposes a new attribute control chart for nonconforming proportions incorporating overdispersion with a beta-binomial model. Methods: Statistical theories for control chart developed under the beta-binomial model and a new approach using this control chart are presented Results: False alarm probabilities of p chart with the beta-binomial model are evaluated and demerits of p chart under overdispersion are discussed from three examples. Hence a concrete procedure for the proposed control chart is provided and illustrated with examples Conclusion: The proposed chart is more useful than traditional p chart, individual chart to treat observed proportions nonconforming as variable data and Laney p' chart.

• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.4
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• pp.383-395
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• 2008

The grouting is one of the improved techniques which is aim to decrease the permeability and to strengthen the soft ground. But The grouting method has many problems about a suitability of grouting procedure and an effectiveness of grouting after grouting work because of a technical characteristic operated inside the soil. The grouting $p{\sim}q{\sim}t$ chart of a typical index about grouting rate and time alteration of grouting pressure is one method to estimate the suitability of grouting factor with monitoring during grouting procedure. This study is automatic grouting system (AGS) which can control the testing and grouting procedures. It can make the detailed $p{\sim}q{\sim}t$ chart and analyze the grouting characters of the ground by comparing the detailed pattern of $p{\sim}q{\sim}t$ chart with standard pattern. If using the $p{\sim}q{\sim}t$ chart derived from AGS in the grouting work, it is an objective standard estimating the suitability of grouting factor with grouting materials, grouting method, grouting rate and grouting pressure, as results it expects successfully to improve reliability of the grouting work.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.75-80
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• 1998

Process information is known to have the continuous distribution in many manufacturing processes. Generalized p-chart has been developed for controlling processes by classifying the information characteristics into several groups. But it is improper to describe continuous processes with the classified process informal ion, which is based on the classical set concept. Fuzzy control chart, has been developed for the control of linguistic data, but it is also based on the dichotomous notion of classical set theory. In this paper, fuzzy sampling method is studied in order to process the uncertain data properly. The method is incorporated with the fuzzy control chart. Statistical characteristics of the fuzzy representative value are utilized to device the fuzzy-statistical control chart. The fuzzy-statistical control chart is compared with the generalized p-chart and both the sensitivity to the process information distribution change pared robustiness against the noise on the process information of the fuzzy-statistical control chart are shown to be superior.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.7
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• pp.1044-1055
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• 2000

The purpose of this study is to suggest sizing chart for a clean room wear. 3 control dimensions(Stature, Bust girth, B.N.P.∼Wrist point length) were chosen as 3 axes of clean room wear size chart. A loss function was used to determined intervals of stature, Bust girth and B.N.P.∼Wrist point length of size chart, because the loss function introduces the concept of frequency to size chart for better customer's size satisfaction. From the size table whose intervals had been determined by a loss function. The 4 sizes individually were suggested for clean room wear size chart by sex. The 3 sizes individually were suggested for clean room head cover size chart by sex too. The suggested size chart would be considered more feasible than present size chart. Also they are suggested supply reference measurement chart relevant to clean room wear manufacturing for 13 most frequent sizes.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.101-112
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• 2008

As charts to monitor the process fraction defectives, P, in the high-yield processes, Mishima et al. (2002) discussed a synthetic chart, the Synthetic CS chart, which integrates the CS (Confirmation Sample)$_{CCC(\text{Cumulative Count of Conforming})-r}$ chart and the CCC-r chart. The Synthetic CS chart is designed to monitor quality characteristics in real-time. Recently, Kotani et al. (2005) presented the EWMA (Exponentially Weighted Moving-Average)$_{CCC-r}$ chart, which considers combining the quality characteristics monitored in the past with one monitored in real-time. In this paper, we present an alternative chart that is more superior to the $EWMA_{CCC-r}$ chart. It is an integration of the $EWMA_{CCC-r}$ chart and the CCC-r chart. In using the proposed chart, the quality characteristic is initially judged as either the in-control state or the out-of-control state, using the lower and upper control limits of the $EWMA_{CCC-r}$ chart. If the process is not judged as the in-control state by the $EWMA_{CCC-r}$ chart, the process is successively judged, using the $EWMA_{CCC-r}$ chart. We compare the ANOS (Average Number of Observations to Signal) of the proposed chart with those of the $EWMA_{CCC-r}$ chart and the Synthetic CS chart. From the numerical experiments, with the small size of inspection items, the proposed chart is the most sensitive to detect especially the small shifts in P among other charts.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.74-85
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• 1997

In this paper we calculate the subgroup size necessary for detecting the change of percent defective with several detection probabilities for orginal population fraction nonconforming p, changed population fraction nonconforming $p^*$, and the ratio k=$p^*$/p in the usage of p control charts. From our calculation we can know the error level of normal a, pp.oximation in detection probability calculation and recommend the subgroup size with lower error levels of normal a, pp.oximation, and then we show the reasonable subgroup size necessary for p, $p^*$, k, and the detection probability of the change of fraction nonconforming in a process. The information that we here show in tables will be useful when p control chart users decide the subgroup size in the p control chart users decide the subgroup size in the p control chart.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.75-81
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• 2005

Borror et al. discussed the EWMA(Exponentially Weighted Moving Average) chart to monitor the count of defects which follows the Poisson distribution, referred to the $EWMA_c$ chart, as an alternative Shewhart c chart. In the $EWMA_c$ chart, the Markov chain approach is used to calculate the ARL (Average Run Length). On the other hand, in order to monitor the process fraction defectives P in high-yield processes, Xie et al. presented the CCC(Cumulative Count of Conforming)-r chart of which quality characteristic is the cumulative count of conforming item inspected until observing $r({\geq}2)$ nonconforming items. Furthermore, Ohta and Kusukawa presented the $CS(Confirmation Sample)_{CCC-r}$ chart as an alternative of the CCC-r chart. As a more superior chart in high-yield processes, in this paper we present an $EWMA_{CCC-r}$ chart to detect more sensitively small or moderate shifts in P than the $CS_{CCC-r}$ chart. The proposed $EWMA_{CCC-r}$ chart can be constructed by applying the designing method of the $EWMA_C$ chart to the CCC-r chart. ANOS(Average Number of Observations to Signal) of the proposed chart is compared with that of the $CS_{CCC-r}$ chart through computer simulation. It is demonstrated from numerical examples that the performance of proposed chart is more superior to the $CS_{CCC-r}$ chart.

• Journal of Korean Society for Quality Management
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• v.44 no.1
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• pp.167-180
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• 2016

Purpose: The problem for the traditional control chart is that it is unable to monitor the very small fraction of nonconforming and the underlying distribution is the normal distribution. $Z_p$ control chart is useful where it controls the vert small fraction on nonconforming. In this study, we will design the $Z_p$ control chart in order to use under non-normal process. Methods: $Z_p$ is calculated not by failure rate based on attribute data but using variable data. Control limit for non-normal $Z_p$ control chart is designed based on ${\alpha}$-risk calculated by cumulative distribution function of Burr distribution. ${\beta}$-risk, which is for performance evaluation, obtains in the Burr distribution's cumulative distribution function and control limit. Results: The control limit for non-normal $Z_p$ control chart is designed based on Burr distribution. The sensitivity can be checked through ARL table and OC curve. Conclusion: Non-normal $Z_p$ control chart is able to control not only the very small fraction of nonconforming, but it is also useful when $Z_p$ distribution is non-normal distribution.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.1
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• pp.67-71
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• 2010

Purpose: The effect of two different levels of illumination and the effect of three letter chart types on subjective refraction findings were investigated. Methods: This study involved thirty Malay university students aged between 19 to 23 years old (7 males, 23 females), with their spherical refractive error ranged between plano to -7.75D astigmatism ranged from plano to -1.75D, anisometropia less than 1D and with no history of ocular injury and pathology. Monocular subjective refraction was measured under two levels of illumination (with and without room light) and with three different letter charts (Snellen letter chart, wall mounted letter chart and projected letter chart). Subjective refraction finding was calculated in spherical equivalent in unit diopter (D). Results: There was no significant effect in the subjective refraction findings with Snellen letter chart (t-test=0.15, p-value=0.88), projected letter chart (t-test=-0.19, p-value=0.85) as well as wall mounted letter chart (t-test=0.12, p-value=0.94). One Way ANOVA also revealed when the subjective refractive measures were compared under two different level of room illumination (with and without room light), no significant effect of letter chart types on subjective refraction readings with room light ($F_{2.185}$=0.11, p-value=0.89) and without room light ($F_{2.185}$=0.02, p-value=0.98). Conclusions: Subjective refraction findings were not affected whether the room light was on or off. They were also not affected by the types of letter chart used.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.167-174
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• 2012

In the manufacturing process the most widely used $\bar{X}$ chart has been applied to control the process mean. Also, Accelerated Life Test(ALT) is commonly used for efficient assurance of product life in development phases, which can be applied in production reliability acceptance test. When life data has lognormal distribution, through censored ALT design so that censored ALT data has asymptotic normal distribution, $ALT\bar{X}$ control chart integrating $\bar{X}$ chart and ALT procedure could be applied to control the mean of process in the manufacturing process. In the situation that process variation is controlled, $Z_p$ control chart is an effective method for the very small fraction nonconforming of quality characteristic. A simultaneous control scheme with $ALT\bar{X}$ control chart and $Z_p$ control chart is designed for the very small fraction nonconforming of product lifetime.