• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.620-623
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• 1996

POSCO has been developed a general purpose dynamic simulator of the hot strip steel mill. The simulator is a tool for developing the process control system in an industrial system solution business, by making the most use of control and simulation techniques fostered in steelmaking business. This simulator has, not only a powerful numerical analysis function, but an easy-to-use graphic user interface which readily enables to simulate dynamic system. This paper presents the features of the simulator and steel rolling process simulator as its application.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.64-71
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• 1995

The objective of this paper is to realize an analysis system that is capable of controlling the quality of an entire cutting process by including a 3 coordinate measuring machine in the process line. Fuzzy reasoning networks based on fuzzy associative memories has been intro- duced in the measuring process, the control limits for the control process have been obtained, and the efficiency and reliability of the system have been determined by examining the simu- lated reasoning control values.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.453-458
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• 2000

Design of an in-process feedback control system has been studied for precision grinding. A grinding system consists of a grinding tool, a turn table and a disk-shaped workpiece on the table is taken as an object. A grinding process model has been deduced which gives some reasoning about the process errors. In the control system the tool position is actively controlled by an electro-magnetic actuator in-process. The ground error is feedback to compose a closed-loop control system and an optimal PID controller is applied. Some control performances such as transient response and disturbance such as transient response and disturbance attenuation have been examined, which convinces the effectiveness of the control. Some methods for implementation of the control. Some methods for implementation of the control have been suggested from a standpoint of practical application.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.108.2-108
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• 2001

This paper presents the application of adaptive phase-locked loop (adaptive PLL) technique to control the process variable of the process control system. The adaptive algorithm is related to the error. When the error of the system is changed, the adaptive gain will be directly changed according to the error. If the value of the adaptive gain is large, the value of the error will be large. In this experiment, the reference input is 50% step input. The experimental result in controlling the first order lag process by the adaptive PLL shows that the response of the controlled system has no overshoot, short rise time, and zero steady-state error. The experimental result also shows that when the output disturbance enters to the process control system, the adaptive PLL can maintain the stability of the system and the effect of the output disturbance can also be fast rejected. The adaptive PLL has better performance ...

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.174-182
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• 2002

System identification and controller formulation are essential in dynamic process control. In system identification, data for system identification are obtained, and then they are analyzed so that the system model of the process is built, identified, and diagnosed. In controller formulation, the control equation is derived based on the result of the system identification. There has been much theoretical research on system identification and controller formulation. These theories are very useful when they are appropriately applied. To our regret, however, these theories are not always effectively applied in practice because the engineers and the operators who manage the process often do not have the necessary understanding of required time series analysis methods. On the other hand, because of widespread use of statistical packages, system identification such as estimating ARMA models can be done with little understanding of time series analysis methods. Therefore, it might be said that the most theoretically difficult part in practice is the controller formulation. In this paper, lists of control equations are proposed as a useful tool for practitioners to use. The tool supports bridging the gap between theory and practice in dynamic process control. Also, for some models, the generalized control equations are obtained.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.1
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• pp.7-16
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• 2003

At present, company has to produce a product that consumer like with a competitive price, a good quality, and a fitting time to supply. Process control and quality control are very important to supply with a product uniformly and inexpensively. Process control is given much weight in the quality control in manufacturing system. Statistical process controls(SPC) that are used in process generally have major impact on manufacturing, product design activities, and process development potentially. Control charts in statistical process control method can be interpreted the data from quality characteristics in production process and discriminated between chance variation and assignable variation in process. In addition, control chart can be used to monitor the process output and detect when changes in the inputs are required to bring the process back to an in-control state. The models that relate the influential inputs to process outputs help determine the nature and magnitude of the adjustments required. In this paper, the characteristic of product quality is monitored by control chart during the machining process and construction of quality control cycle is considered to divide into two types in this case that different assignable causes lead to shifts having different magnitudes. Then we are intended to find a process shift magnitude which has economical quality cost policy and are considered to quality cost functions to find a process shift magnitude. Those costs are categorized into the well-known categories of prevention, appraisal, and internal failure and external failure. This paper ends with numerical examples that demonstrate the usefulness of the model.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.665-665
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• 2005

The existing DSP for utility interactive photovoltaic generation system control generally uses floating point process type. Because it is easy to use for number crunching, however, it is too late and too expensive. Fixed point process DSP TMS320F2812, has high control speed and is rather inexpensive. A very complicated real system can be simulated using hardware-in-the-loop (HIL) system in a virtual environment Therefore, HIL system can speed up research and development process with a little effort. Also current DSP for utility interactive photovoltaic generation system adopts floating point process type, which is easy to use for number crunching. However, fixed point process DSF, TMS320F2812, has high control speed and is rather inexpensive. This paper presents more efficient method for MPPT control using TMS320F2812 along with HIL System.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2001.11a
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• pp.142-147
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• 2001

Recently, as the field of construction industrial is enlarged and the blanket control system is formed, the process plan considered from initial process formation to construction cost must be systematic and rational. So we have to propose and compose the new process formation system that divides the intention decisive property of construction data, its relationship and the data property according to process definitely and can express and control easily the public ownership of construction data and network process under the peculation control. So this study decides the field formation and construction data of the work according to the ordering and contract way to establish the process data system for the process plan, shows that the lot theory is necessary to form the economical construction field and proposes that the integrated formation system of construction data that is made by code system must be established.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.73-85
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• 1997

In the product liability age the demand on quality is extremely high and inspection and test are automated. The process capability indices $C_p, {\;}C_{pk}$ and p control chart widely used to provide unitless measure of process performance and process control. Traditional process capability indices $C_p, {\;}C_{pk}$ do not represent the process variation from target value. The convention p chart for control of fraction nonconforming becomes inadequate when the fraction nonconforming becomes very small such as PPM level production system. This paper proposes process performance measure considering quadratic loss function and cumulative counts control chart for control of PPM level production system.