• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.338-341
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• 1996

A neural fuzzy control strategy, developed in order to make a Mobile Vehicle(MV) run along with the traffic guidelines on the road, is presented. A neurocomputer is used in the control procedure and it learnt the driving knowledge to control the MV's actions. The image information of the guidelines is provided by a CCD camera on the top of the MV. The MV utilize the image information to identify the shape of the road and to decide the position of itself, and control the running actions. A fuzzy controller works on-line. Both of the neural controller and the fuzzy controller make up each other. This control method solve the problem of mechanical and electrical inertia and make the Mobile Vehicle run rapidly and smoothly.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.54-67
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• 2005

This paper provides an evaluation of an optimization-based, multiple-input double-output (MIDO) run-to-run (R2R) control scheme for general semiconductor manufacturing processes. The controller in this research, termed adaptive dual response optimizing controller (ADROC), can serve as a process optimizer as well as a recipe regulator between consecutive runs of wafer fabrication. In evaluation, it is assumed that the equipment model could be appropriately described by a pair of second-order polynomial functions in terms of a set of controllable variables. Of practical relevance is to consider a drifting effect in the equipment model since in common semiconductor practice the process tends to drift due to machine aging and tool wearing. We select a typical application of R2R control to chemical mechanical planarization (CMP) in semiconductor manufacturing in this evaluation, and there are five different CMP process scenarios demonstrated, including mean shift, variance increase, and IMA disturbances. For the controller, ADROC, an on-line estimation technique is implemented in a self-tuning (ST) control manner for the adaptation purpose. Subsequently, an ad hoc global optimization algorithm based on the dual response approach, arising from the response surface methodology (RSM) literature, is used to seek the optimum recipe within the acceptability region for the execution of next run. The main components of ADROC are described and its control performance is assessed. It reveals from the evaluation that ADROC can provide excellent control actions for the MIDO R2R situations even though the process exhibits complicated, nonlinear interaction effects between control variables, and the drifting disturbances.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.1
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• pp.12-18
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• 2008

This paper describes two run-to-run controllers, a nonlinear multiple exponential-weight moving-average (NMEWMA) controller and a dynamic model-tuning minimum-variance (DMTMV) controller, for photolithography processes. The relationships between the input recipes (exposure dose and focus) and output variables (critical dimensions) were formed using an experimental design method, and the photolithography process model was built using a multiple regression analysis. Both the NMEWMA and DMTMV controllers could update the process model and obtain the optimal recipes for the next run. Quantified improvements were obtained from simulations and real photolithography processes.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.101-106
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• 2014

New control charts under repetitive sampling are proposed, which can be used for variables and attributes quality characteristics. The proposed control charts have inner and outer control limits so that repetitive sampling may be needed if the plotted statistic falls between the two limits. Particularly, the new np and variable X-bar control charts under repetitive sampling are considered in detail. The in-control and out-of-control average run lengths are analyzed according to various process shifts. The performance of the proposed control charts is compared with the existing np and the X-bar control charts in terms of the average run lengths.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.14-20
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• 2004

The coefficient of variation(CV) which is a relatively dimensionless measure of variability is widely used to describe the variation of sample data. However, the properties of CV distribution are little available and few research has been done on estimation and interpretation of CV. In this paper, we give an outline of statistical properties of coefficient of variation and design of control chart based on this statistic. Construction procedures of control chart are presented. The proposed control chart is an efficient method to monitor a process variation for short production run situation. Futhermore, we evaluated the performance of CV control chart by average run length(ARL).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1128-1133
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• 2014

Most of the statistical signal analysis processed in the time domain and the frequency domain are based on the assumption that the signal is weakly stationary(wide sense stationary). Therefore, it is necessary to know whether the surface EMG signals processed in the statistical basis satisfy the condition of the weak stationarity. The purpose of this study is to find optimal segment length of surface EMG signal for assessing stationarity with the modified Run-test and RA-test. Ten stationary surface EMG signals were simulated by AR(autoregressive) modeling, and ten real surface EMG signals were recorded from biceps brachii muscle and then modified to have non-stationary structures. In condition of varying segment length from 20ms to 100ms, stationarity of the signals was tested by using six different methods of modified Run-test and RA-test. The results indicate that the optimal segment length for the surface EMG is 30ms~35ms, and the best way for assessing surface EMG signal stationarity is the modified Run-test (Run2) method using this optimal length.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.6151-6158
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• 2013

Radio frequency ablation (RFA) is an effective means of achieving local control of liver cancer. It is a particularly suitable mode of therapy for small and favorably located tumors. However, local progression rates are substantially higher for large tumors (>3.0 cm). In the current study, we report on a mathematical model based on geometric optimization to treat large liver tumors. A database of mathematical models relevant to the configuration of liver cancer was also established. The specific placement of electrodes and the frequency of ablation were also optimized. In addition, three types of liver cancer lesion were simulated by computer guidance incorporating mathematical models. This approach can be expected to provide a more effective and rationale mechanism for employing RFA in the therapy of hepatic carcinoma.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.8
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• pp.452-458
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• 2016

The study on pH control at the themophilic solubilization (pretreatment process) was investigated in order to improve the methane gas production of two phase anaerobic digestion of food waste. From a batch experiment, it was observed that the solubilization efficiency was increased from 26.2% to 47.1% and 55.6% by the pH increament from $4.20{\pm}0.40$ (without pH control) to $7.00{\pm}0.50$, and $12.00{\pm}0.50$, respectively. However there was immaterial increase (8.5%) in solubilization efficiency when the pH was increased from $7.00{\pm}0.50$ to $12.00{\pm}0.50$. The two phase anaerobic digestion system was operated for laboratory scale experiment under the solubilization condition of pH $4.20{\pm}0.40$ (Run1) and $7.00{\pm}0.50$ (Run2). Higher soluble chemical oxygen demand (SCOD) and total volatile fatty acid (TVFA) concentration were observed in Run2 throughout the system resulted by the solubilization effect at the pH $7.00{\pm}0.50$. The TVFA concentration in acidogenic reactor was 18.4 g/L which was 1.8 times higher than the result of Run1. Consequently the methane gas production was enhanced to 0.333 L/g VS in the methanogenic reactor, which is 18% higher than the result (0.282 L/g VS) of Run1.

• Journal of Energy Engineering
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• v.25 no.2
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• pp.37-44
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• 2016

The demand for electricity has a considerable impact on various energy sectors since electricity is generated from various energy sources. This paper attempts to estimate the electricity demand function and obtain some quantitative information on price and income elasticities of the demand. To this end, we apply a lagged dependent variable model to derive long-run as well as short-run elasticities using the time-series data over the period 1991-2014. Our dependent variable is annual electricity demand. The independent variables include constant term, real price of electricity, and real gross domestic product. The results show that the short-run price and income elasticities of the electricity demand are estimated to be -0.142 and 0.866, respectively. They are statistically significant at the 5% level. That is, the electricity demand is in-elastic with respect to price and income changes in the short-run. The long-run price and income elasticities of the electricity demand are calculated to be -0.210 and 1.287, respectively, which are also statistically meaningful at the 5% level. The electricity demand is still in-elastic with regard to price change in the long-run. However, the electricity demand is elastic regarding income change in the long-run. Therefore, this indicates that the effect of demand-side management policy through price-control is restrictive in both the short- and long-run. The growth in electricity demand following income growth is expected to be more remarkable in the long-run than in the short-run.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.2
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• pp.62-67
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• 2000

The uniformity of temperature on a wafer is one of the most important parameters to control the RTP (Rapid Thermal Process) with proper input signals. Since it is impossible to achieve the uniformity of temperature without exact estimation of temperature at all points on the wafer, the difficulty of understanding internal dynamics and structural complexities of the RTP is a primary obstacle to accurately measure the distributed temperatures on the wafer. Furthermore, it is also hard to accomplish desirable estimation because only few pyrometers have been commonly available in the general equipments. In the paper, a thermal model based on the chamber geometry of the AST SHS200 RTP system is developed to effectively control the thermal uniformity on the wafer. First of all, the estimation method of one-point measurement is developed, which is properly extended to the case of multi-point measurements. This thermal model is validated through certain simulation and experiments. The work can be usefully contributed to building a run-by-run or a real-time controls of the RTP.