• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10B
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• pp.936-944
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• 2006

In order to enhance their own customer satisfaction index that is one of the top level managerial performance indices, Internet communication service providers endeavor onto establishing a total quality management system. Specifically, it is under discussion that some critical Internet communication network quality characteristics closely related to customer satisfaction index should be controlled aiming to this managerial goal. This paper presents an application scheme of I-MR control charts for monitoring Internet communication network quality characteristics. This statistical quality control scheme generates a signal to practitioners when it detects the network quality characteristics out-of control. It is designed based on; 1) individual measurements; and 2) moving ranges between two consecutive individual measurements collected with a constant time interval. Empirical analyses are illustrated to estimate the expected quality improvement ratios that can be realized with the application scheme proposed in this paper. Assuming that the assignable causes can be revealed and eradicated, regarding two Internet communication services A, B, seven network quality characteristics for each service, eleven distinct measuring spots for each network quality characteristic, the expected quality improvement ratios are calculated with which the effect of the application scheme is evaluated. Results show the ranges of the expected quality improvement ratios; 1) Service A, (1) mean (0.31%-11.44%), (2) standard deviation (9.82%-71.10%): 2) Service B, (1) mean (0.29%-17.64%), (2) standard deviation (8.05%-60.59%). Hence, It is anticipated that the I-MR control charts based application scheme can be effective not only to improving the mean and dispersion of the network quality characteristics concerned but also to maintaining the network quality characteristics in-control consequently.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.903-913
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• 2013

Social network services generate a considerable amount of social data every day on personal feelings or thoughts. This social data provides changing patterns of information production and consumption but are also a tool that reflects social phenomenon. We analyze negative emotional words from daily blogs to detect the change in blooger sentiment using multivariate control charts. We used the all the blogs produced between 1 January 2008 and 31 December 2009. Hotelling's T-square control chart control chart is commonly used to monitor multivariate quality characteristics; however, it assumes that quality characteristics follow multivariate normal distribution. The performance of a multivariate control chart is affected by this assumption; consequently, we introduce the support vector data description and its extension (K-control chart) suggested by Sun and Tsung (2003) and they are applied to detect the chage in blogger sentiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.971-972
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.643-644
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• 2013

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.69-76
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• 1999

A new statistic {{{{ {d }`_{2 } ^{s } }}}} is introduced for constructing co ntrol limits. It is easier and more convienient than d2 We will show the characteristic of {{{{ {d }`_{2 } ^{s } }}}} and evaluate {{{{ {d }`_{2 } ^{s } }}}} through average run length(ARL).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.157-166
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• 1997

Classical SPC charting methods such as (equation omitted), R, S charts assume high volume manufacturing processes where at least 25 or 30 calibrate samples of size 4 or 5 each can be gathered to estimate the process parameters before on-line charting actually begines. However, for many processes, especially in a job-shop setting, production runs are not necessarily long and charting technique are required that do not that depend upon knowing the process parameters in advance of the run. In this paper, using modifying statistics, we give a method for constructing control charts for the process mean when the measurements are from a normal distribution. In this case, consider that smaller weight being assigned to the older data as time process and properties and taking method of exponential smoothing constant$(\lambda)$ are suggested.

• Journal of Korean Institute of Industrial Engineers
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• v.6 no.2
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• pp.31-36
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• 1980

This paper proposes a very simple algorithm for determining the parameters in the economic design of s-charts. These parameters are the sample size, the factor determining the spread of the control limit and the sampling interval. Several examples show that the parameters determined by this algorithm are very close to the exact optimal values.

• Journal of Korean Institute of Industrial Engineers
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• v.4 no.2
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• pp.59-66
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• 1978

This paper is a work scheduling for design of piping Department of chemical plant using accumulated curve. Accumulated curve prepared by analysis of performance data, collected executed manhours for chemical plant of "D" Company during the past two years. It compared scheduled manhours with actual used manhours up to six months, put into the form of figures and charts the results can he summarized as below; 1) It can he found an important factor of critical control thus piping department got 30% of total scheduled menhours. 2) A plan of manpower mobilization can be scheduled before work starting. 3) Project progress can he found easily as put into the form of figures and charts for schedule to actual.

• Journal of the Korea Safety Management & Science
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• v.11 no.1
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• pp.131-136
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• 2009

The research develops the calculation steps of Z sigma level, process capability index(PCI) and process performance index(PPI) applicable to the discrete process in the service industry. The paper presents three following topics used related process indexes according to the precision and accuray in the continuous process. The contents include diverse process indexs for nonconformities by SPC attribute control charts and bias coefficient. The same technique of the nonconformites is also used in the nonconforming units. The practical examples are provided to help easier understanding for users.

• The Journal of Engineering Geology
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• v.19 no.3
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• pp.261-268
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• 2009

Tunnel measurements provide crucial information on the ground stability during the excavation, visualizing the ground behavioral characteristics with quantitative dada. Generally, the frequency of the measurements is greater during the early stage of the tunnelling process and reduced with time. However, there are no quantitative criteria established for either the activities, such as the time, location and frequency of the measurement or the management guidance, especially for the site of subtle and unexpected displacement during the excavation. It is, however, still challenging to assess behavioral characteristics of subtle and unexpected displacement after stabilization. In this study, we propose a new method to assess stability and to analysis the behavioral characteristics of subtle and unexpected displacement after stabilization using statistic control charts of displacements. We also present a test result on the applicability of control chart and CUSUM control chart to measured displacements.