• Title/Summary/Keyword: Use of Control Charts

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Development of Short-Run Standardized Control Charts and Acceptance Control Charts Classified by the Demand Volume and Variety (수요량과 다양성 패턴에 의해 유형화된 단기간 표준화 관리도와 단기간 합격판정 관리도의 개발)

  • Choi, Sung-Woon
    • Journal of the Korea Safety Management & Science
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    • v.12 no.4
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    • pp.255-263
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    • 2010
  • The research developes short-run standardized control charts(SSCC) and short-run acceptance control charts(SACC) under the various demand patterns. The demand patterns considered in this paper are three types such as high-variety and repetitive low-volume pattern, extremely-high-variety and nonrepetitive low-volume pattern, and high-variety and extremely-low-volume pattern. The short-run standardized control charts developed by extending the long-run ${\bar{x}}$-R, ${\bar{x}}$-s and I-MR charts have strengths for practioners to understand and use easily. Moreover, the short-range acceptance control charts developed in the study can be efficiently used through combining the functions of the inspection and control chart. The weighting schemes such as Shewhart, moving average (MA) and exponentially weighted moving average (EWMA) can be considered by the reliability of data sets. The two types according to the use of control chart are presented in the short-range standardized charts and acceptance control charts. Finally, process capability index(PCI) and process performance index(PPI) classified by the demand patterns are presented.

Multiparameter CUSUM charts with variable sampling intervals

  • Im, Chang-Do;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.3
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    • pp.593-599
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    • 2009
  • We consider the problem of using control charts to monitor more than one parameter with emphasis on simultaneously monitoring the mean and variance. The fixed sampling interval (FSI) control charts are modified to use variable sampling interval (VSI) control charts depending on what is being observed from the data. In general, approaches of monitoring the mean and variance simultaneously is to use separate charts for each parameter and a combined chart. In this paper, we use three basic strategies which are separate Shewhart charts for each parameter, a combined Shewhart chart and a combined CUSUM chart. We showed that a combined VSI CUSUM chart is comparatively more efficient than any other chart if the shifts in both mean and variance are small.

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Multivariate control charts based on regression-adjusted variables for covariance matrix

  • Kwon, Bumjun;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.937-945
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    • 2017
  • The purpose of using a control chart is to detect any change that occurs in the process. When control charts are used to monitor processes, we want to identify this changes as quickly as possible. Many problems in quality control involve a vector of observations of several characteristics rather than a single characteristic. Multivariate CUSUM or EWMA charts have been developed to address the problem of monitoring covariance matrix or the joint monitoring of mean vector and covariance matrix. However, control charts tend to work poorly when we use the highly correlatted variables. In order to overcome it, Hawkins (1991) proposed the use of regression adjustment variables. In this paper, to monitor covariance matrix, we investigate the performance of MEWMA-type control charts with and without the use of regression adjusted variables.

Design of Acceptance Control Charts According to the Process Independence, Data Weighting Scheme, Subgrouping, and Use of Charts (프로세스의 독립성, 데이터 가중치 체계, 부분군 형성과 관리도 용도에 따른 합격판정 관리도의 설계)

  • Choi, Sung-Woon
    • Journal of the Korea Safety Management & Science
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    • v.12 no.3
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    • pp.257-262
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    • 2010
  • The study investigates the various Acceptance Control Charts (ACCs) based on the factors that include process independence, data weighting scheme, subgrouping, and use of control charts. USL - LSL > $6{\sigma}$ that used in the good condition processes in the ACCs are designed by considering user's perspective, producer's perspective and both perspectives. ACCs developed from the research is efficiently applied by using the simple control limit unified with APL (Acceptable Process Level), RLP (Rejectable Process Level), Type I Error $\alpha$, and Type II Error $\beta$. Sampling interval of subgroup examines i.i.d. (Identically and Independent Distributed) or auto-correlated processes. Three types of weight schemes according to the reliability of data include Shewhart, Moving Average(MA) and Exponentially Weighted Moving Average (EWMA) which are considered when designing ACCs. Two types of control charts by the purpose of improvement are also presented. Overall, $\alpha$, $\beta$ and APL for nonconforming proportion and RPL of claim proportion can be designed by practioners who emphasize productivity and claim defense cost.

Multivariate CUSUM control charts for monitoring the covariance matrix

  • Choi, Hwa Young;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.2
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    • pp.539-548
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    • 2016
  • This paper is a study on the multivariate CUSUM control charts using three different control statistics for monitoring covariance matrix. We get control limits and ARLs of the proposed multivariate CUSUM control charts using three different control statistics by using computer simulations. The performances of these proposed multivariate CUSUM control charts have been investigated by comparing ARLs. The purpose of control charts is to detect assignable causes of variation so that these causes can be found and eliminated from process, variability will be reduced and the process will be improved. We show that the charts based on three different control statistics are very effective in detecting shifts, especially shifts in covariances when the variables are highly correlated. When variables are highly correlated, our overall recommendation is to use the multivariate CUSUM control charts using trace for detecting changes in covariance matrix.

Comparison of the Unbiasing Constants in Connection with Variable Control Charts (계량형 관리도와 관련된 불편화 상수의 비교)

  • Ahn, Haeil
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.4
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    • pp.134-144
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    • 2014
  • With the advent of lean-six sigma era, an extensive use of analytic tools such as control charts is required in the field of manufacturing. In relation to statistical quality control (SQC) or process control (SPC), the Korean standards have undergone a meaningful change. In this study, the theoretic backgrounds for evaluating the control limits in connection with the variable control charts are examined in view of better understanding the related constants and coefficients. This paper is intended to help the quality control practitioners understand the mathematical backgrounds by comparing related quality control constants and also to encourage them to make use of and to take the advantage of the variable control charts which are very useful for implementing the concept of lean-six sigma in many industrial sites.

Bootstrap control limits of process control charts for correlative process data

  • Suzuki Hideo
    • Proceedings of the Korean Society for Quality Management Conference
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    • 1998.11a
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    • pp.174-179
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    • 1998
  • This research explores the application of the bootstrap methods to the construction of control limits for the x charts and the EWMA charts based on single observations with stationary autoregressive processes. The subsample means-based control chars in the presence autocorrelation are also considered. We use a technique for inferring confidence intervals using bootstrap, the percentile method. Simulation studies are conducted to compare the performance of the bootstrap method and that of standard method for constructing control charts under several conditions.

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Control Charts for Ordinal Variables (순서형 변수를 위한 관리도)

  • Jang, Dae-Heung
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2006.04a
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    • pp.330-333
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    • 2006
  • Many practical problems of quality control in service management are derived from the use of ordinal variables. Ordered linguistic variables differ from measurement variables. This paper presents a new control chart of a production process based on ordinal variables.

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The Z-CUSUM Control Chart for the Process with Recurring Cycles or Frequent Small Shifts (순환 주기나 빈번한 작은 이동이 발생하는 공정관리를 위한 Z-CUSUM 관리도)

  • Kang Hae Woon;Kang Chang Wook;Paik Jae Won
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2004.04a
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    • pp.57-63
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    • 2004
  • CUSUM control charts are widely used to monitor processes with small shifts. CUSUM control charts, however, are less effective in detecting for recurring cycles or frequent small shifts in the process. With Shewhart control charts, we have applied the variety of run rules to check the stability of process in addition to the situations that some points fall outside the control limits. In this paper, we propose the Z-CUSUM control chart for monitoring the process with recurring cycles or frequent small shifts by use of the zone concept as like the Shewhart control charts.

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The Z-CUSUM Control Chart for the Process with Recurring Cycles or Frequent Small Shifts (순환주기나 빈번한 작은 이동이 발생하는 공정관리틀 위한 Z-CUSUM 관리도)

  • 강해운;강창욱;백재원
    • Journal of Korean Society for Quality Management
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    • v.32 no.2
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    • pp.132-153
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    • 2004
  • CUSUM control charts are widely used to monitor processes with small shifts. CUSUM control charts are, however, less effective in detecting for recurring cycles or frequent small shifts in the processes. With Shewhart control charts, we have applied the variety of run rules to check the stability of process in addition to the situations that some points fall outside the control limits. In this paper, we propose the Z -CUSUM control chart for monitoring the process with recurring cycles or frequent small shifts by use of the zone concept as like the Shewhart control charts.