• Title/Summary/Keyword: run probability

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Median Control Chart for Nonnormally Distributed Processes (비정규분포공정에서 메디안특수관리도 통용모형설정에 관한 실증적 연구(요약))

  • 신용백
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.10 no.16
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    • pp.101-106
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    • 1987
  • Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the $\bar{X}$-chart, $\bar{X}$-chart, $\bar{X}$-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In Shewhart $\bar{X}$-chart. which is the most widely used one in Kora, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for the more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, Truncated-normal distributions. Robustness of the proposed median control chart is compared with that of the $\bar{X}$-chart; the former tends to be superior to the latter as the probability distribution of the process becomes more skewed. The average run length to detect the assignable cause is also compared when the process has a Normal or a Gamma distribution for which the properties of X are easy to verify, the proposed chart is slightly worse than the $\bar{X}$-chart for the normally distributed product but much better for Gamma-distributed products. Average Run Lengths of the other distributions are also computed. To use the proposed control chart, the probability distribution of the process should be known or estimated. If it is not possible, the results of comparison of the robustness force us to use the proposed median control chart based oh a normal distribution. To estimate the distribution of the process, Sturge's formula is used to graph the histogram and the method of probability plotting, $\chi$$^2$-goodness of fit test and Kolmogorov-Smirnov test, are discussed with real case examples. A comparison of the proposed median chart and the $\bar{X}$ chart was also performed with these examples and the median chart turned out to be superior to the $\bar{X}$-chart.

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An Analysis on the Identification Rate of Detection System Using Non-Homogeneous Discrete Absorbing Markov Chains (비 동질성 이산시간 흡수마코프체인을 활용한 탐지체계의 식별률 분석에 관한 연구)

  • Kim, Seong-Woo;Yoon, Bong-Kyoo
    • Journal of the Korean Operations Research and Management Science Society
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    • v.40 no.2
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    • pp.31-42
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    • 2015
  • The purpose of airborne radars is to detect and identify approaching targets as early as possible. If the targets are identified as enemies, detection systems must provide defense systems with information of the targets to counter. Though many previous studies based on the detection theory of the target have shown various ways to derive detection probability of each radar, optimal arrangement of radars for effective detection, and determination of the search pattern, they did not reflect the fact that most military radar sites run multiple radars in order to increase the accuracy of identifications by radars. In this paper, we propose a model to analyze the probability of identification generated by the multiple radars using non-homogeneous absorbing markov chains. Our results are expected to help the military commanders counter the enemy targets effectively by using radars in a way to maximize the identification rate of targets.

Run related probability function and their application to start-up demonstration tests

  • Bi, Yi-Ming;Oh, Jung-Taek;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.4
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    • pp.1067-1074
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    • 2016
  • A start-up demonstration test is a mechanism that is usually used to determine the reliability of equipment, for example water pumps, car batteries and power generators. The simplest and oldest start-up demonstration tests are called CS (consecutive successes) which have been studied by Hahn and Gage (1983), Viveros and Balakrishnan (1993).At first Hahn and Gage (1983) discussed the start-up demonstration test. I was based on i.i.d (independently and identically distributed) binary outcomes with the specified number of consecutive successful start-ups. Oh (2016) studied CSNCF (consecutive successful, but not consecutive failures). In this paper, we investigated the CS and CSNCF models, also their applications to start-up demonstration tests. The numerical results showed that the expectations and variances of the total number of attempted start-ups until the acceptance of the unit are gradually increasing in all of the specified number of successes as the p (probability of a successful start-up in an single trial) decreases from 0.99 to 0.90. The difference between means of the CS mode and CSNCF model is small, but variances of the CS and CSNCF are big.

Influence of Joint Distribution of Wave Heights and Periods on Reliability Analysis of Wave Run-up (처오름의 신뢰성 해석에 대한 파고_주기결합분포의 영향)

  • Lee Cheol-Eung
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.17 no.3
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    • pp.178-187
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    • 2005
  • A reliability analysis model f3r studying the influence of joint distribution of wave heights and periods on wave un-up is presented in this paper. From the definition of failure mode related to wave run-up, a reliability function may be formulated which can be considered uncertainties of water level. In particular, the reliability analysis model can be directly taken into account statistical properties and distributions of wave periods by considering wave period in the reliability function to be a random variable. Also, variations of wave height distribution conditioned to mean wave periods can be taken into account correctly. By comparison of results of additional reliability analysis using extreme distributions with those resulted from joint distribution of wave height and periods, it is found that probabilities of failure evaluated by the latter is larger than those by the former. Although the freeboard of sloped-breakwater structures can be determined by extreme distribution based on the long-term measurements, it may be necessary to investigate additionally into wave run-up by using the present reliability analysis model formulated to consider joint distribution of a single storm event. In addition, it may be found that the effect of spectral bandwidth parameter on reliability index may be little, but the effect of wave height distribution conditioned to mean wave periods is straightforward. Therefore, it may be confirmed that effects of wave periods on the probability of failure of wave run-up may be taken into account through the conditional distribution of wave heights. Finally, the probabilities of failure with respect to freeboard of sloped-breakwater structures can be estimated by which the rational determination of crest level of sloped-breakwater structures may be possible.

Geometric charts with bootstrap-based control limits using the Bayes estimator

  • Kim, Minji;Lee, Jaeheon
    • Communications for Statistical Applications and Methods
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    • v.27 no.1
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    • pp.65-77
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    • 2020
  • Geometric charts are effective in monitoring the fraction nonconforming in high-quality processes. The in-control fraction nonconforming is unknown in most actual processes; therefore, it should be estimated using the Phase I sample. However, if the Phase I sample size is small the practitioner may not achieve the desired in-control performance because estimation errors can occur when the parameters are estimated. Therefore, in this paper, we adjust the control limits of geometric charts with the bootstrap algorithm to improve the in-control performance of charts with smaller sample sizes. The simulation results show that the adjustment with the bootstrap algorithm improves the in-control performance of geometric charts by controlling the probability that the in-control average run length has a value greater than the desired one. The out-of-control performance of geometric charts with adjusted limits is also discussed.

Control of G/MX/1 Queueing System with N-Policy and Customer Impatience

  • Lim, Si-Yeong;Hur, Sun
    • Industrial Engineering and Management Systems
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    • v.15 no.2
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    • pp.123-130
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    • 2016
  • We introduce a queueing system with general arrival stream and exponential service time under the N-policy, where customers may renege during idle period and arrival rates may vary according to the server's status. Probability distributions of the lengths of idle period and busy period are derived using absorbing Markov chain approach and a method to obtain the optimal control policy that minimizes long-run expected operating cost per unit time is provided. Numerical analysis is done to illustrate and characterize the method.

EWM-MR chart for individual measurements in start-up process (초기공정에서 개별관측치를 이용한 EWM-MR 관리도)

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

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Switching properties of bivariate Shewhart control charts for monitoring the covariance matrix

  • Gwon, Hyeon Jin;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.6
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    • pp.1593-1600
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    • 2015
  • A control chart is very useful in monitoring various production process. There are many situations in which the simultaneous control of two or more related quality variables is necessary. We construct bivariate Shewhart control charts based on the trace of the product of the estimated variance-covariance matrix and the inverse of the in-control matrix and investigate the properties of bivariate Shewart control charts with VSI procedure for monitoring covariance matrix in term of ATS (Average time to signal) and ANSW (Average number of switch) and probability of switch, ASI (Average sampling interval). Numerical results show that ATS is smaller than ARL. From examining the properties of switching in changing covariances and variances in ${\Sigma}$, ANSW values show that it does not switch frequently and does not matter to use VSI procedure.

Switching properties of CUSUM charts for controlling mean vector

  • Chang, Duk-Joon;Heo, Sun-Yeong
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.859-866
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    • 2012
  • Some switching properties of multivariate control charts are investigated when the interval between two consecutive sample selections is not fixed but changes according to the result of the previous sample observation. Many articles showed that the performances of variable sampling interval control charts are more efficient than those of fixed sampling interval control charts in terms of average run length (ARL) and average time to signal (ATS). Unfortunately, the ARL and the ATS do not provide any information on how frequent a switch is being made. We evaluate several switching properties of two sampling interval Shewhart and CUSUM procedures for controlling mean vector of correlated quality variables.

Switching properties of multivariate Shewhart control charts

  • Kim, Bo-Jung;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.4
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    • pp.911-925
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    • 2017
  • We investigate the properties of multivariate Shewart control charts with VSI procedure for monitoring simultaneous monitoring mean vector and covariance matrix in term of ANSW (average number of switches), probability of switch and ASI (average sampling interval), ATS (average time to signal). From examining the ANSW values, we know that it does not switch frequently. The VSI control charts are superior to the corresponding FSI control charts in terms of ATS. And, it can be also seen that the VSI procedures have substantially fewer switches for small or moderate shifts of the mean vector and variances.