• Title/Summary/Keyword: Bar Chart

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Economic Analysis for Detection of Out-of-Control of Process Using 2 of 2 Runs Rules (2중 2 런규칙을 사용한 공정이상 감지방법의 경제성 분석)

  • Kim, Young Bok;Hong, Jung Sik;Lie, Chang Hoon
    • Journal of Korean Institute of Industrial Engineers
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    • v.34 no.3
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    • pp.308-317
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    • 2008
  • This research investigates economic characteristics of 2 of 2 runs rules under the Shewhart $\bar{X}$ control chart scheme. A Markov chain approach is employed in order to calculate the in-control average run length (ARL) and the average length of analysis cycle. States of the process are defined according to the process conditions at sampling time and transition probabilities are derived from the state definitions. A steady state cost function is constructed based on the Lorezen and Vance(1986) model. Numerical examples show that 2 of 2 runs rules are economically superior to the Shewhart $\bar{X}$ chart in many cases.

Economic Adjustment Design For $\bar{X}$ Control Chart: A Markov Chain Approach

  • Yang, Su-Fen
    • International Journal of Quality Innovation
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    • v.2 no.2
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    • pp.136-144
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    • 2001
  • The Markov Chain approach is used to develop an economic adjustment model of a process whose quality can be affected by a single special cause, resulting in changes of the process mean by incorrect adjustment of the process when it is operating according to its capability. The $\bar{X}$ control chart is thus used to signal the special cause. It is demonstrated that the expressions for the expected cycle time and the expected cycle cost are easier to obtain by the proposed approach than by adopting that in Collani, Saniga and Weigang (1994). Furthermore, this approach would be easily extended to derive the expected cycle cost and the expected cycle time for the case of multiple special causes or multiple control charts. A numerical example illustrates the proposed method and its application.

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$\bar{X}$ Control Chart Pattern Identification Through Efficient Neural Network Training (효율적인 신경회로망 학습을 이용한 $\bar{X}$ 관리도의 이상패턴 인식에 관한 연구)

  • 김기영;유정현;윤덕균
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.45
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    • pp.365-374
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    • 1998
  • Control Chart is a powerful tool to detect that process is in control or out of control. CIM can have real effect when CIM involve automated quality control. A neural network approach is used for unnatural pattern detecting of control chart. The previous moving window method uses all unnatural pattern that is detected as moving time window. Therefore, It trains a large number of unnatural pattern and takes training time long. In this paper, the proposed method tests a small number of training unnatural pattern which modifies test data without repeating time. We shows that the proposed method has differences In training time and identification rate on the previous moving windows method. As results, we reduced training time and obtain the same identification rate.

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Statistical Design of X Control Chart with Improved 2-of-3 Main and Supplementary Runs Rules (개선된 3 중 2 주 및 보조 런 규칙을 가진 X관리도의 통계적 설계)

  • Park, Jin-Young;Seo, Sun-Keun
    • Journal of Korean Society for Quality Management
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    • v.40 no.4
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    • pp.467-480
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    • 2012
  • Purpose: This paper introduces new 2-of-3 main and supplementary runs rules to increase the performance of the classical $\bar{X}$ control chart for detecting small process shifts. Methods: The proposed runs rules are compared with other competitive runs rules by numerical experiments. Nonlinear optimization problem to minimize the out-of-control ARL at a specified shift of process mean for determining action and warning limits at a time is formulated and a procedure to find two limits is illustrated with a numerical example. Results: The proposed 2-of-3 main and supplementary runs rules demonstrate an improved performance over other runs rules in detecting a sudden shift of process mean by simultaneous changes of mean and standard deviation. Conclusion: To increase the performance in the detection of small to moderate shifts, the proposed runs rules will be used with $\bar{X}$ control charts.

Application of Dynamic $\bar{x}$-R Control Chart for Advanced Phase Isolation Ditch (APID) Process (APID공정 내 공정진단을 위한 dynamic $\bar{x}$-R 관리도의 적용)

  • An, Sang-Woo;Kwak, Sung-Keun;Jung, Young-Wook;Chung, Mu-Keun;Park, Jae-Woo
    • Journal of Korean Society on Water Environment
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    • v.25 no.5
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    • pp.704-712
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    • 2009
  • Advanced Phase Isolation Ditch (APID) process was studied to develop economic retrofitting technology, for the plants where retrofitting of common activated sludge process is required. In this study, to evaluate and monitor the effluent water quality ($BOD_5$, SS, T-N, and T-P) and operating conditions (Influent, SVI, SRT, and HRT) as process capable and stable parameters for treating municipal wastewater, a demonstration plant was installed and operated in the existing sewage treatment plant of P city. During this study, the average effluent $BOD_5$, SS, T-N, and T-P concentrations were 7.7, 5.6, 10.8, and 1.6 mg/L. Trend analysis of influent $BOD_5$, SS, T-N, and T-P in APID process were illustrated that APID process need for more strong APID process management on the winter session, such as developing new intermediated aeration mode, operating methods, and managements strategy. At the application of control chart, the signal of uncommon effects at APID process was determined much higher existing control chart tntr conventional control chart in this study. These results indicate that conventional control chart has been collected and determined cleary signal at only stable situation. Therefore, newly developed APID process of dynamic control chart can be one of the useful tool for monitoring and management process.

An Effective Design of Process Mean Control Chart in Subgroups Based on Cluster Sampling Type

  • Nam, Ho-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.939-950
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    • 2003
  • Control charts are very useful tool for monitoring of process characteristics. This paper discusses the problem of design of control limits when the subgroups are composed by cluster sampling type. As an alternative method of design of control limits XbBar chart is proposed, which uses the control limits based on the variation between subgroups instead of using classical variation within subgroups. Two examples are presented for reasonable design of control limits and conditions of subgroups based on the cluster sampling. Through examples the guidelines for making proper control limits are proposed.

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Design of Median Control Chart for Unsymmetrical Weibull Distribution (비대칭(非對稱)와이블분포공정(分布工程)에서 메디안특수관리도(特殊管理圖)의 설계(設計))

  • Sin, Yong-Baek;Hwang, Ui-Mi
    • Journal of Korean Society for Quality Management
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    • v.14 no.2
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    • pp.2-8
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    • 1986
  • This thesis is concerned with the design of control chart based on the sample median which is easy to use in practical situations and to analyze the properties for non-normally distributed Weibull process. In this cases are use to the quality characteristics of the process are not normally distributed but skewed due to the intermitted production, small lot size and sample size is small one n=3 or n=5, etc. And when it relates unsymmetrically distributed process, model designed median control chart is more effective than Shewhart $\bar{x}$-chart which assumed on normal distribution, when we exactly should be known Weibull distribution or estimated. The median control chart in this thesis is more robustness compared with other conventionally developed control chart.

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Modified Multivariate $T^2$-Chart based on Robust Estimation (로버스트 추정에 근거한 수정된 다변량 $T^2$- 관리도)

  • 성웅현;박동련
    • Journal of Korean Society for Quality Management
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    • v.29 no.1
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    • pp.1-10
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    • 2001
  • We consider the problem of detecting special variations in multivariate $T^2$-control chart when two or more multivariate outliers are present. Since a multivariate outlier may reflect slippage in mean, variance, or correlation, it can distort the sample mean vector and sample covariance matrix. Damaged sample mean vector and sample covariance matrix have difficulty in examining special variations clearly, An alternative to detection outliers or special variations is to use robust estimators of mean vector and covariance matrix that are less sensitive to extreme observations than are the standard estimators $\bar{x}$ and $\textbf{S}$. We applied popular minimum volume ellipsoid(MVE) and minimum covariance determinant(MCD) method to estimate mean vector and covariance matrix and compared its results with standard $T^2$-control chart using simulated multivariate data with outliers. We found that the modified $T^2$-control chart based on the above robust methods were more effective in detecting special variations clearly than the standard $T^2$-control chart.

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An Economic-Statistical Design of Moving Average Control Charts

  • Yu, Fong-Jung;Chin, Hsiang;Huang, Hsiao Wei
    • International Journal of Quality Innovation
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    • v.7 no.3
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    • pp.107-115
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    • 2006
  • Control charts are important tools of statistical quality control. In 1956, Duncan first proposed the economic design of $\bar{x}-control$ charts to control normal process means and insure that the economic design control chart actually has a lower cost, compared with a Shewhart control chart. An moving average (MA) control chart is more effective than a Shewhart control chart in detecting small process shifts and is considered by some to be simpler to implement than the CUSUM. An economic design of MA control chart has also been proposed in 2005. The weaknesses to only the economic design are poor statistics because it dose not consider type I or type II errors and average time to signal when selecting design parameters for control chart. This paper provides a construction of an economic-statistical model to determine the optimal parameters of an MA control chart to improve economic design. A numerical example is employed to demonstrate the model's working and its sensitivity analysis is also provided.