• Journal of the Korean Society of Safety
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• v.7 no.4
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• pp.33-43
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• 1992

A methodology to develop an expert system for chemical plant fault diagnosis based on functional-structure of chemical plant is proposed. A methodology to generalize and utilize the heuristic know-edge of plant operators is also developed. A plant can be seen as a Hierarchical set of subsystems. Each subsystem is called a SCOPE. The state of the plant and the behavior of each subsystem is managed by the SCOPES. An expert system based on this functional structure and knowledge base has been developed and ar plied to the subprocess of etylene plant to evaluate the effectiveness of the methodology.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.431-436
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• 1986

The design and manufacture of injection molded polymeic parts with desired mechanical properties is a costly process dominated by empiricism, including the modification of actual tooling. This paper presents an interactive computer-based design system for injection molded plastic parts. This knowledge-based synthesis system provides a rational design strategy for injection molding and molded parts. It synergistically combines a rule-based expert system for hurestic knowledge with analytical process simulation programs. The theremomechanical properties of a molded part such as the effect of molecular orientation and weldline strength are predicted by the analysis programs; while the expert system interprets the analytical results from the process simulation, evaluates the design, and generates recommendations for optimal design alternatives. The heuristic knowledge of injection molding is formalized as production rules of the expert consultation system.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.70-72
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• 1993

This paper presents an expert system that sheds loads considering priority in the localized SCADA power systems during an emergency states. The proposed algorithm uses neural networks to detect local load shedding location and heuristic rules to determine load shedding amounts. The proposed expert system is demonatrated at one of the model system which incorporates two localized SCADA power system. It is operated under workstation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.565-572
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• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.2
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• pp.323-338
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• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.61-68
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• 2001

A rotor system is composed of a rotating shaft with supporting bearings. The rotor system is widely used in every rotating machinery such as the turbine generator and the high precision machine tools. A negligible error or malfunction in the rotor, however, can cause a catastrophic failure in the system then result in the environmental and economic disasters. A diagnosis of the rotor system is important in preventing these kinds of failures and disasters. Up to now, many researchers have devoted in the development of diagnosing tools for the system. The basic principles behind the tools are to retrieve the data through the sensors for a specific state of the system and then to identify the specific state through the heuristic methods such as neural network, fuzzy logic, and decision matrix. The proper usage of the heuristic methods will enhance the performance of the diagnostic procedure when together used with the statistical signal processing. In this paper, the methodologies in using the above 3 heuristic methods for the diagnostics of the rotor system are established and also tested and validated for the data retrieved from the rolling element bearing and journal bearing supported system.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.47-64
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• 2008

It is well known that consumer's quality perception is strongly affected by price. Higher priced products tend to be perceived to have better quality than lower priced products although the objective product quality is the same. However, it is less known the process through which quality perception is affected by price cues. The existing literature suggests three potential hypotheses (i.e., the selectiveprocessing hypothesis, the selective interpretation hypothesis, and the representativeness heuristic hypothesis) that explain the underlying processes of the price-induced quality perception. The current research tests among the three competing hypotheses and also examines the role of consumer knowledge as a moderating factor. An experiment was conducted to test the moderating role of the knowledge in the price-quality relationship and to investigate the underlying process. The results indicate that theinfluence of price on perceived quality differs between novices and experts. Expert consumers' quality perception is not significantly influenced by price and this finding is consistent with the extant literature. On the other hand, novice consumers' quality perception is affected by price and the tests on the underlying process support for the representativeness heuristic hypothesis. Novice consumers assess that a high-priced brand should have good product quality due to the belief that high (low) price brands represent better (worse) brand quality and such a representativeness heuristic occurs without involving selective attention or selective interpretation price-consistent information.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.75-82
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• 1991

This research is concerned with Machine-Part Group Formation(MPGF) methodology for Flexible Manufacturing Systems(FMS). The purpose of the research is to develop a new heuristic algorithm for effectively solving MPGF problem. The new algorithm is proposed and evaluated by 100 machine-part incidence matrices generated. The performance measures are (1) grouping ability of mutually exclusive block-diagonal form. (2) number of unit group and exceptional elements, and (3) grouping time. The new heuristic algorithm has the following characteristics to effectively conduct MPGF : (a) The mathematical model is presented for rapid forming the proper number of unit groups and grouping mutually exclusive block-diagonal form, (b) The simple and effective mathematical analysis method of Rank Order Clustering(ROC) algorithm is applied to minimize intra-group journeys in each group and exceptional elements in the whole group. The results are compared with those from Expert System(ES) algorithm and ROC algorithm. The results show that the new algorithm always gives the group of mutually exclusive block-diagonal form and better results(85%) than ES algorithm and ROC algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.1
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• pp.1-5
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• 2000

This paper presents a new algorithm to restore the de-energized loads in electric power distribution systems for restoration by utilizing object-based structure and heuristic rules without branch and feeder overloading. In order to cope with a complex network configuration and frequent breaker switching operations in distribution systems, the component of power system is described as objects and the information of system configuration is constructed by connecting objects each other. Such a strategy is developed mainly based on the object search algorithm to increase computation efficiency. As a result, the proposed system has been implemented to efficiently deal with large distribution systems by reducing computational burden remarkably compared with the conventional methods.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.99-106
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• 1998

In this paper, we have constructed an expert system for semiconductor chip encapsulation which combines a knowledge-based system with CAE software. The knowledge-base module includes heuristic and pre analysis knowledge for evaluation and redesign. Evaluation of the initial design and generation of redesign recommendations can be developed from the rules as applied to a given chip package. The CAE programs can be used for simulating the filling and packing stage of encapsulation process. The expert system is a new tool which enables package design or process conditions with high yields and high productivity.