• Title, Summary, Keyword: statistical process control

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An Integrated Process Control Scheme Based on the Future Loss (미래손실에 기초한 통합공정관리계획)

  • Park, Chang-Soon;Lee, Jae-Heon
    • The Korean Journal of Applied Statistics
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    • v.21 no.2
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    • pp.247-264
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    • 2008
  • This paper considers the integrated process control procedure for detecting special causes in an ARIMA(0,1,1) process that is being adjusted automatically after each observation using a minimum mean squared error adjustment policy. It is assumed that a special cause can change the process mean and the process variance. We derive expressions for the process deviation from target for a variety of different process parameter changes, and introduce a control chart, based on the generalized likelihood ratio, for detecting special causes. We also propose the integrated process control scheme bases on the future loss. The future loss denotes the cost that will be incurred in a process remaining interval from a true out-of-control signal.

The Economic Design of VSS $\bar{x}$ Control Chart for Compounding Effect of Double Assignable Causes (두 가지 복합 이상원인 영향이 있는 공정에 대한 VSS$\bar{x}$관리도의 경제적 설계)

  • Sim Seong-Bo;Kang Chang-Wook;Kang Hae-Woon
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.27 no.2
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    • pp.114-122
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    • 2004
  • In statistical process control applications, variable sample size (VSS) $\bar{X}$ chart is often used to detect the assignable cause quickly. However, it is usually assumed that only one assignable cause results in the out-of-control in the process. In this paper, we propose the algorithm to minimize the function of cost per unit time and compare the economic design and the statistical design by use of the value of cost per unit time. We consider double assignable causes to occur with compound in the process and adopt the Markov chain approach to investigate the statistical properties of VSS $\bar{X}$ chart. A procedure that can calculate the control chart's parameters is proposed by the economic design.

Design of Combined Shewhart-CUSUM Control Chart using Bootstrap Method (Bootstrap 방법을 이용한 결합 Shewhart-CUSUM 관리도의 설계)

  • 송서일;조영찬;박현규
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.25 no.4
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    • pp.1-7
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    • 2002
  • Statistical process control is used widely as an effective tool to solve the quality problems in practice fields. All the control charts used in statistical process control are parametric methods, suppose that the process distributes normal and observations are independent. But these assumptions, practically, are often violated if the test of normality of the observations is rejected and/or the serial correlation is existed within observed data. Thus, in this study, to screening process, the Combined Shewhart - CUSUM quality control chart is described and evaluated that used bootstrap method. In this scheme the CUSUM chart will quickly detect small shifts form the goal while the addition of Shewhart limits increases the speed of detecting large shifts. Therefor, the CSC control chart is detected both small and large shifts in process, and the simulation results for its performance are exhibited. The bootstrap CSC control chart proposed in this paper is superior to the standard method for both normal and skewed distribution, and brings in terms of ARL to the same result.

A Study on the manufacturing process using the sensitivity analysis of stochastic network (감도분석에 의한 제조공정연구)

  • 박기주
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.24 no.63
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    • pp.65-77
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    • 2001
  • A more technical perspective is needed in estimating the effect of the Manufacturing Process for improving the Productivity, there are many statistical evaluation methods, convenience sampling, frequencies, histogram, QC seven tools, control chart etc. It is more important for the companies to use six sigma to reduce defective and improve the process control than the technical definition as a disciplined quantitative approach for improvement of process control and a new way of quality innovation. Process network analysis is a technique which has the potentiality for a wide use to improve the manufacturing process which other techniques can't be used to analyze effectively. It has some problems to analyze the process with feedback loops. The branch probabilities during quality inspections depend upon the number of times the product has been rejected. This paper presents how to improve the manufacturing process by statistical process control using branch probabilities, Moment Generating Function(MGF) and Sensitivity Equation.

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Estimation of the Change Point in VSS X Control Charts

  • Lee, Jaeheon;Park, Changsoon
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.825-833
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    • 2003
  • Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a maximum likelihood estimator of the process change point when a Shewhart $\bar{X}$ chart with variable sample size (VSS) scheme signals a change in the process mean. Also we build a confidence interval for the process change point by using the likelihood function.

Use of Statistical Process Control for Quality Assurance in Radiation Therapy (방사선치료에서의 품질보증을 위한 통계적공정관리의 활용)

  • Cheong, Kwang-Ho
    • Progress in Medical Physics
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    • v.26 no.2
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    • pp.59-71
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    • 2015
  • The goal of quality assurance (QA) is to minimize systematic errors in order to maintain the quality of a certain process. Statistical process control (SPC) has been utilized for QA in radiation therapy field since 2005 and is changing QA paradigm. Its purpose is to maintain a process within the given control limits while monitoring of error trends such as variation or dispersion. SPC can be applied to all QA aspects of radiotherapy; however, a medical physicist should have enough knowledge about the application of SPC to QC/QA procedures. In this paper, the author introduce a concept of SPC and review some previously reported studies those used SPC for QA in radiation therapy.

A Study on the Statistical Production Control of Energy Efficiency in Electric Product (전기제품 에너지 소비효율의 통계적 양산 관리 방법에 대한 연구)

  • Chun, Young-Ho;Kim, Seong-Don
    • Journal of the Korea Management Engineers Society
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    • v.23 no.4
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    • pp.73-86
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    • 2018
  • Most electric products produced during the manufacturing process are produced after design and mass production under a given control standard. In particular, the development phase should present the criteria for the production process by setting appropriate limits based on the performance being targeted. Even if the standard of performance is set considering the performance of the process, measuring the performance of the product after actual production results will cause nonconformities with the expected results. Among the performance of electrical products, Energy standards represented by energy consumption efficiency continue to be of importance, and are mandatory standards that correspond to national standards in most countries. Therefore, statistical quality control of these standards shall basically have a large number of test equipment for each product, ensure sufficient test time and continuous sampling of product samples. In the end, companies that produce and sell electric appliances are striving to control mass production at a great cost, but this is not acceptable. This study presents basic characteristics of the energy efficiency of electrical products and proposes and conducts a case study on statistical production control methods for performance variation across products under the standards about domestic and international regulations.

An Economic Design of the Integrated Process Control Procedure with Repeated Adjustments and EWMA Monitoring

  • Park Changsoon;Jeong Yoonjoon
    • Proceedings of the Korean Statistical Society Conference
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    • pp.179-184
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    • 2004
  • Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This article considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process disturbance model under consideration is an IMA(1,1) model with a location shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied by compensating the predicted deviation from target. For detecting special causes the two kinds of exponentially weighted moving average (EWMA) control chart are applied to the observed deviations: One for detecting location shift and the other for detecting increment of variability. It was assumed that the adjustment of the process under the presence of a special cause may change any of the process parameters as well as the system gain. The effectiveness of the IPC scheme is evaluated in the context of the average cost per unit time (ACU) during the operation of the scheme. One major objective of this article is to investigate the effects of the process parameters to the ACU. Another major objective is to give a practical guide for the efficient selection of the parameters of the two EWMA control charts.

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Statistical Process Control and Adjustment using Process Incapability Index (공정비능력지수를 이용한 통계적 공정관리와 조정)

  • 구본철
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.24 no.63
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    • pp.45-54
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    • 2001
  • The process capability indices have been widely used in manufacturing industries to provide numerical measures of process potential and performance. This study is concerned with process controls and adjustments by incapability index $C_{pp}$ and its sub-indices. A monitoring for $\^{C}_{pp}$ would provide a convenient way to monitor changes on process capability after statistical control is established, since $C_{pp}$ simultaneously measures process variability and centering. Further, we can separate charting of process location and variability by sub-indices of $C_{pp}$, ($C_{ia}$, $C_{ip}$), without returning to $\={x}$-R chart, even though an out-of-control signals on $\^{C}_{pp}$ control chart is found.

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Optimal Designs for Attribute Control Charts

  • Chung, Sung-Hee;Park, Sung-Hyun;Park, Jun-Oh
    • Proceedings of the Korean Statistical Society Conference
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    • pp.97-103
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    • 2003
  • Shewhart-type control charts have historically been used for attribute data, though they have ARL biased property and even are unable to detect the improvement of a process with some process parameters. So far most efforts have been made to improve the performance of attribute control charts in terms of faster detection of special causes without increasing the rates of false alarm. In this paper, control limits are proposed that yield an ARL (nearly) unbiased chart for attributes. Optimal design is also proposed for attribute control charts under a natural sense of criterion.

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