• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.237-249
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• 1998

Process adjustment has been widely used in production processes in order to set the output characteristic as close as to the target. Box and Kramer(1992) developed a feedback adjustment control procedure for process adjustment. We generalize their procedure by using a rational subgrouping of sequential observations. In this paper the feedback control rule of the rational subgrouping is proposed and the overall expected cost is evaluated. Also properties of the proposed control scheme are illustrated and compared to Box and Kramer's in the context of the expected cost.

• Journal of Korean Society for Quality Management
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• v.31 no.2
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• pp.183-193
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• 2003

A special cause producing temporary deviation in the underlying process can influence on process adjustment in responsive feedback control system. In this paper, the impact of special causes on the EWMA(Exponentially Weighted Moving Average) forecasts and the process adjustment that is based on the EWMA forecasts are derived. For some special causes with patterned type of contamination, the influence of the causes on the output process are explicitly investigated. A data set, contaminated by a special cause of level shift, is analyzed to evaluate the impact numerically.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.237-246
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• 1999

An important problem in process adjustment using feedback is how often to sample the process and when to apply an adjustment. Schemes designed to minimize the overall cost. The cost taken the frequency with which they require observations to be made, and the resulting overall length of time between adjustment. In this article, the process adjustment which is based on the adaptive EWMA forecasts are derived. An example is presented to improve confirm standard varation through the analysis of a data series.

• Journal of the Korea Safety Management & Science
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• v.1 no.1
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• pp.111-121
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• 1999

An important problem in process adjustment using feedback is how often to sample the process and when to apply an adjustment. Schemes are designed to minimize the overall cost. The cost is taken the frequency with which they require observations to be made, and the resulting overall length of time between adjustments. In this article, the process adjustment which is based on the adaptive EWMA forecasts is derived. An example is presented to improve the standard variation through the analysis of data series.

• Journal of Korean Society for Quality Management
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• v.32 no.2
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• pp.201-211
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• 2004

Process adjustment is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.425-429
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• 2004

Process adjustment Is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.

• The Journal of Korean Physical Therapy
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• v.12 no.1
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• pp.65-71
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• 2000

This study investigated the effect of anticipatory postural adjustment on balance performance in postural disturbance. Any action performed by standing subject is generally accompanied by compensatory postural activities, which reduce or abolish the postural disturbance generated by the movement and keep the subjects' center of gravity within the supporting base. These Postural activities arc triggered by either anticipatory and feedback postural control. We studied the difference of anticipatory and feedback postural control in postural disturbance. The subjects were standing on a foot plate with eyes closed, holding a lead of $5\%$ of their own body weight in their hands. The condition of anticipatory postural adjustment was applied voluntarily releases the a load. The condition of feedback postural control was applied that the load was unpredictably removed. We concluded that anticipatory postural adjustment becomes more efficient to postural performance in postural disturbance.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.49-55
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• 2007

A special cause producing temporary deviation in the underlying process can influence on process adjustment in First-Order System feedback control system. In this paper, the impact of special causes on the forecasts and the process adjustment that is based on the EWMA forecasts are derived for a first-order system. For some special causes with patterned type of contamination, the influence of the causes on the output process are explicitly investigated. A data set, contaminated by a special cause of level shift, is analyzed to confirm the impact numerically.

• Journal of the Korea Safety Management & Science
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• v.2 no.4
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• pp.19-32
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• 2000

Assignable causes producing temporary deviation from the underlying system can influence on process adjustment and process monitoring in dynamic feedback control system. In this paper, the impact of assignable causes on EWMA forecasts and process adjustment which is based on the EWMA forecasts are derived for optimum control methods.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.2
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• pp.67-72
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• 1996

This paper presents a parameter adaptive control law that stabilizes and asymptotically regulates any single-input, linear time-invariant, controllable and observable, discrete-time system when only the upper bounds on the order of the system is given. The algorithm presented in this paper comprises basically a nonlinear state feedback law which is represented by functions of the state vector in the controllable subspace of the model, an adaptive identifier of plant parameters which uses inputs and outputs of a certain length, and an adaptive law for feedback gain adjustment. A new psedu-inverse algorithm is used for the adaptive feedback gain adjustment rather than a least-square algorithm. The proposed feedback law results in not only uniform boundedness of the state vector to zero. The superiority of the proposed algorithm over other algorithms is shown through some examples.