• Journal of Korean Institute of Industrial Engineers
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• v.29 no.3
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• pp.239-246
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• 2003

Individual items are produced continuously from an industrial process. Each item is checked to determine whether it satisfies a lower screening limit for the quality characteristic which is the weight of an expensive ingredient. If it does, it is sold at a regular price; if it does not, it is reprocessed or sold at a reduced price. The process mean may be adjusted to a higher value in order to reduce the proportion of the nonconforming items. Using a higher process mean, however, may result in a higher production cost. In this paper, the optimal process mean and lower screening limit are determined in situations where the probability that an item functions well is given by a logistic function of the quality characteristic. Profit models are constructed which involve four price/cost components; selling prices, cost from an accepted nonconforming item, and reprocessing and inspection costs. Methods of finding the optimal process mean and lower screening limit are presented and numerical examples are given.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.200-207
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• 2011

The research which sees accomplishes the capital region high-speed railway and examines investigates about process of railroad construction project and an advance service contents from to understand a progress process, change process and technical investigation of basic design and the execution plan at the time of route led and accomplishes the plan which is detailed the process which in the center researched. Also plan start method and application plan, clear the security of the plan air which is proper is necessary and dividing which design phase is, plan process construction etc. improvements sacrifice froze.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.84-89
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• 2003

Fuzzy controller is one of the succeed controller used in the process control in case of model uncertainties. But it my be difficult to fuzzy controller to articulate the accumulated knowledge to encompass all circumstance. Hence, it is essential to provide a tuning capability. There are many parameters in fuzzy controller can be adapted, scale factor tuning of normalized fuzzy controller is one of the adaptation parameter. Two adaptation methods are implemented in this work on an experimental thermal process, which simulate heating process in liquefied petroleum gases (LPG) recovery process in one of petrochemical industries: Gradient decent (GD) adaptation method; supervisory fuzzy controller. A comparison between the two methods is discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1718-1723
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• 1991

The determination of a production sequence is an important problem in a batch process operation. In this paper a new algorithm for a near optimal production sequence of N product in an M unit serial multiproduct batch process is proposed. The basic principle is the same as that of Johnson's algorithm for two-unit UIS system. Test results on a number of selected examples exhibit the superiority over previously reported results. In addition, a tabulation technique is presented to calculate the makespan of a given sequence of production for all processing units under UIS mode.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.654-659
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• 1993

In this paper, a robot controller that has a real time-multitasking OS (Operating System) is developed. It can do given jobs in realtime, so its effectiveness is increased. The controller has several CPU boards, and it is needed to communicate among these boards. For that reason, it is adopted VME bus system and VMEexec OS that can process multiprocess in realtime. Multiprocess includes robot language edit process, vision process, low level motion control process, and teach process in higher layer. And dynamics, kinematics, and inverse kinematics that require realtime calculation are included in lower layer.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.879-884
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• 1988

For more economical operation of chemical plants, optimal operating conditions are to be set and maintained as far as possible. For this purpose, optimizing control is applied to chemical plants. In this study, a process optimizer composed of a process simulator and an optimization routine using Successive Quadratic Programming as optimization technique is developed and the effect of optimizing control is tested on an example process, and a new process optimization strategy based on modified Jacobian matrix is developed.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.639-646
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• 2012

The exponential continuous time GARCH(p,q) model for financial assets suggested by Haug and Czado (2007) is considered, where the log volatility process is driven by a general L$\acute{e}$vy process and the price process is then obtained by using the same L$\acute{e}$vy process as driving noise. Uniform ergodicity and ${\beta}$-mixing property of the log volatility process is obtained by adopting an extended generator and drift condition.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.4 no.1
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• pp.24-29
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• 2005

The development of an aluminum bumper is required in order to reduce the weight of the automobile. An porthole die extrusion process is simulated by the finite element method in order to develop the aluminum bumper which is manufactured by hollow section extrusion. The general-purpose finite element analysis software is used. The developed analysis method can be applied to the optimization of the porthole die extrusion process for the aluminum bumper.

• Journal of the Semiconductor & Display Technology
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• v.5 no.4 s.17
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• pp.29-34
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• 2006

In order to design an OLED(Organic Luminescent Emitting Device) evaporation system, geometric simulation of film thickness distribution profile is required. For the OLED evaporation process, thin film thickness uniformity is of great practical importance. In this paper, a geometric modeling algorithm is introduced for process simulation of the OLED evaporating process. The physical fact of the evaporating process is modeled mathematically. Based on the developed method, the thickness of the thin-film layer can be successfully controlled.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.381-399
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• 2004

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC re-duces 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 paper considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an IMA(1,1) model with a step 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 according to the predicted deviation from target. For detecting special causes the exponentially weighted moving average control chart is applied to the observed deviations. It was assumed that the adjustment under the presence of a special cause may increase the process variability or change the system gain. Reasonable choices of parameters for the IPC procedure are considered in the context of the mean squared deviation as well as the average run length.