• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1480-1489
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• 1996

In ATM networks there are two methods in traffic control as schemes advancing the quality of service. One is reactive control after congestion and the other which is generally recommended, is preventive control before congestion, including connection admission control on call leel and usage parameter control, network parameter control, priority control and congestion control on cell level. In particular, usage parameter control is required for restricting the peak cell rate of bursy tracffic to the parameter negotiated at call set-up phase since the peak cell rate significantly influences the network quality of service. The scheme for progressing quality of service by usage parameter control is themethod using VSA(Virtual Scheduling Algorlithm) recommended ITU-T. The method using VSSA(Virtual Scheduling Suggested Algorlithm) in this paper is suggested by considering cell delay variation and token rate of leaky bucket, compared VSA and VSANT(Virtual Scheduling Algolithm with No Tolerance) with VSSA which polices violated cell probability of conformed peak cell rate and intentionally excessive peak cell rate. VSSA method using IPP(Interruped Poisson Process) model of input traffic source showed more quality of service than VSA and VSANT methods as usage parameter control because the suggested method reduced the violated cell probability of contformed peak cell rate and intentionally excessive peak cell rate.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.58-67
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• 2002

Since the inception of off-line quality control, it has drawn a particular attention from research community and it has been implemented in a wide variety of industries mainly due to its extensive applicability to numerous real situations. Emphasizing design issues rather than control issues related to manufacturing processes, off-line quality control has been recognized as a cost-effective approach to quality improvement. It mainly consists of three design stages: system design, parameter design, and tolerance design which are implemented in a sequential manner. Utilizing experimental designs and optimization techniques, off-line quality control is aimed at achieving product performance insensitive to external noises by reducing process variability. In spite of its conceptual soundness and practical significance, however, off-line quality control has also been criticized to a great extent due to its heuristic nature of investigation. In addition, it has also been pointed out that the process optimization procedures are inefficient. To enhance the current practice of off-line quality control, this study proposes an integrated optimization model by utilizing a well-established statistical tool, so called response surface methodology (RSM), and a tolerance - cost relationship.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.93-102
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• 2008

In this paper, we propose a rate control algorithm for constant quality real time video coding. To achieve constant quality, previous algorithm exploit mean absolute of difference(MAD) as measure of frame complexity. However, if scene is abruptly changed or if quantization parameter is not constant, encoder produces various output bits with same MAD. Therefore we know that MAD does not appropriately reflect characteristic of frame. To solve this problem, we exploit model parameter as measure of frame complexity. Because model parameter means slope between output bits and MAD, it reflects correctly complexity of frame. And because previous model, R-MAD model, is not considered quantization parameter, as quantization parameter increases or decreases, model parameter of frame also vary. So model parameter obtained using previous model cannot reflect internal characteristic of video. We solve this problem using proposed model, which is considered quantization parameter. Experiment results show that our algorithm provide better performance, in terms of quality smoothness than previous algorithm. Especially, when scene is abruptly changed, our algorithm alleviates quality drop.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1174-1179
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• 2008

Many modeling and calibration methods have been developed to analyze and design the biological wastewater treatment process. For the systematic use of activated sludge model (ASM) in a real treatment process, a most important step in this usage is a calibration which can find a key parameter set of ASM, which depends on the microorganism communities and the process conditions of the plants. In this paper, a standardized calibration protocol of the ASM model is developed. First, a weighted effluent quality index(WEQI) is suggested far a calibration protocol. Second, the most sensitive parameter set is determined by a sensitive analysis based on WEQI and then a parameter optimization method are used for a systematic calibration of key parameters. The proposed method is applied to a calibration problems of the single carbon removal process. The results of the sensitivity analysis and parameter estimation based on a WEQI shows a quite reasonable parameter set and precisely estimated parameters, which can improve the quality and the efficiency of the modeling and the prediction of ASM model. Moreover, it can be used for a calibration scheme of other biological processes, such as sequence batch reactor, anaerobic digestion process with a dedicated methodology.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.67-78
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• 1999

In parameter design introduced by Taguchi, we analyze a performance measure, so called SN ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing performance measures is presented, which can be used to control several quality characteristics simultaneously in parameter design. To develop such multivariate performance measures, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.131-139
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• 2004

Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.117-122
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• 2005

Variable sampling rate(VSR) scheme varies the sampling rate for the current sample depending on the previous value of the control statistic. In this paper, we propose EWMA control charts with variable parameter(VP) scheme, which allows both the sample rate(the sample size or the sampling interval) and the weight to vary. We investigate the effectiveness of the VP scheme relative to the fixed parameter(FP) scheme and the VSR scheme in EWMA control charts. It is shown that using the VP scheme gives some improvements to the ability in detecting small and moderate shifts in the process normal mean.

• Journal of the Korea Safety Management & Science
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• v.1 no.1
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• pp.123-134
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• 1999

There are several models for process quality assurance by quality system (ISO 9000), process capability analysis, acceptance control chart and so on. When a high level process capability has been achieved, it takes a long time to monitor the process shift, so it is sometimes necessary to develop a quicker monitoring system. To achieve a quicker quality assurance model for high-reliability process, this paper presents a model for process quality assurance when the fraction nonconforming is very small. We design an acceptance control chart based on variable quality characteristic and time-censored accelerated testing. The distribution of the characteristics is assumed to be normal or lognormal with a location parameter of the distribution that is a linear function of a stress. The design parameters are sample size, control limits and sample proportions allocated to low stress. These paramaters are obtained under minimization of the relative variance of the MLE of location parameter subject to APL and RPL constraints.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.247-257
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• 1999

There are several models for process quality assurance by quality system(ISO 9000), process capability analysis, acceptance control chart and so on. When a high level process capability has been achieved, it takes a long time to monitor the process shift, so it is sometimes necessary to develop a quicker monitoring system. To achieve a quicker quality assurance model for high-reliability process, this paper presents a model for process quality assurance when the fraction nonconforming is very small. We design an acceptance control chart based on variable quality characteristic and time-censored accelerated testing. The distribution of the characteristics is assumed to be normal of lognormal with a location parameter of the distribution that is a linear function of a stress. The design parameters are sample size, control limits and sample proportions allocated to low stress. These parameters are obtained under minimization of the relative variance of the MLE of location parameter subject to APL and RPL constraints.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.519-530
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• 2015

The geometric chart has proven more effective than Shewhart p or np charts to monitor the proportion nonconforming in high-quality processes. Implementing a geometric chart commonly requires the assumption that the in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice in high-quality process where the proportion of nonconforming items is very small. Thus, the error in the parameter estimation increases and may lead to deterioration in the performance of the control chart if a sample size is inadequate. We suggest adjusting the control limits in order to improve the performance when a sample size is insufficient to estimate the parameter. We propose a linear function for the adjustment constant, which is a function of the sample size, the number of nonconforming items in a sample, and the false alarm rate. We also compare the performance of the geometric charts without and with adjustment using the expected value of the average run length (ARL) and the standard deviation of the ARL (SDARL).