• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.3 s.246
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• pp.219-230
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• 2006

Digital CAD models are one of the most important assets the manufacturer holds. The trend toward concurrent engineering and outsourcing in the distributed development and manufacturing environment has elevated the importance of high quality CAD model and its efficient exchange. But designers have spent a great deal of their time repairing CAD model errors. Most of those poor quality models may be due to designer errors caused by poor or incorrect CAD data generation practices. In this paper, we propose a rule-based approach for healing CAD model errors. The proposed approach focuses on the design history data representation from a commercial CAD model, and the procedural method for building knowledge base to heal CAD model. Through the use of rule-based approach, a CAD model healing system can be implemented, and experiments are carried out on automobile part models.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• The Journal of Information Technology
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• v.5 no.4
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• pp.57-64
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• 2002

The system that is thermal test system for elements has been controlled generally by PID algorithm because of its characteristic. There is not a mathematical model for the system. So the system that is use the PID controller is not properly operated. To solve this problem, we propose a fuzzy algorithm that parameters and rule base is selected by self-searched algorithm for each system. The input fuzzy membership function is adapted based on the set stable range. Output membership function is nearly fixed but some parameter is adjustable. The rule base is changed under basis on the system response. The output value computed through inference and defuzzification is mapped into a value that is proper for the system operation. Through this regulation, it will be possible to prevent the temperature of system to go into the unstable temperature.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.11
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• pp.3091-3097
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• 1994

An expert system for NC part programming of NC lathe (ESPP-1) is developed as a part of Computer-Adied Manufacturing system. Conventional computer-assisted part programming system essentially requires an NC part programmer who is an expert in NC part programming. But the developed ESSP-1 can allow an inexperienced person to make an excellent NC data for the NC Lathe without any problem, since the system has a knowledge base composed of EIA and ISO NC code, feed rate, spindle speed, machining coordinates selection, and tool selection etc., which were directly evoked from some skilled NC part programmers, and referenced some machining handbooks. This paper discusses the algorithm of the expert system for NC part programming of the NC lathe (ESPP-1) and the performance comparisons between the developed expert system and the conventional system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.294-300
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• 2006

This case study shows constructing the knowledge-based system using a rule-based approach for detecting transactions regarding money laundering in the Korea Financial Intelligence Unit (KoFIU). To better manage the explosive increment of low risk suspicious transactions reporting from financial institutions and to conjugate data converged into the KoFIU from various organizations, the adoption of a knowledge-based system is definitely required. We designed and constructed the knowledge-based system for anti-money laundering by committing experts of each specific financial industry co-worked with a knowledge engineer. The outcome of the knowledge base implementation shows that the knowledge-based system is filtering STRs in the primary analysis step efficiently and so has made great contribution to improve efficiency and effectiveness of the analysis process. It can be said that establishing the foundation of the knowledge base under the entire framework of the knowledge-based system for consideration of knowledge creation and management is indeed valuable.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.374-376
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• 2001

In this paper, we developed the fault diagnostic expert system of silicone-immersed transformer using dissolved gas analysis. The knowledge base module consists of the knowledge using the rule: if Then . The inference engine uses the fuzzy rule for the management of uncertainty of the boundary and rule and derivate the Belief and Plausibility of the normality and fault using Dempster-Shafer theory. The expert system is connected to the database and it can manages the history of gas-data of the transformer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.125-132
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• 2011

Fire monitoring system detects a fire based on the values of various sensors, such as smoke, CO, temperature, or change of temperature. It detects a fire by comparing sensed values with predefined threshold values for each sensor. However, to prevent a fire it is required to predict a situation which has a possibility of fire occurrence. In this work, we propose a fire recognition system using a fuzzy inference method. The rule base is constructed as a combination of fuzzy variables derived from various sensed values. In addition, in order to solve generalization and formalization problems of rule base construction from expert knowledge, we analyze features of fire patterns. The constructed rule base results in an improvement of the recognition accuracy. A fire possibility is predicted as one of 3 levels(normal, caution, danger). The training data of each level is converted to fuzzy rules by FCM(fuzzy C-means clustering) and those rules are used in the inference engine. The performance of the proposed approach is evaluated by using forest fire data from the UCI repository.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.1
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• pp.47-57
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• 2010

There have been many problems to apply SPC(Statistical Process Control) which is a traditional process control technology to the process of multi-product, small-sized production because a machine in the process manufactures small numbers, but various kinds of products. Therefore, we need the new process control system that can flexibly control the process by setting up the SPEC rules and the KNOWHOW rules. The SPEC rule contains the combination of diverse conditions to specify the characteristics of various products. The KNOWHOW rule is based on engineers' know-how. The study suggests the Rule-base Process Control that can be optimized to the multi-product, small-sized production. It was validated in the process of semiconductor production.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.119-124
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• 2014

In this paper, we propose the active rule system applying with emotional margin for power saving control. The proposed system in this paper is a part of the system which derives smart power saving by adjusting the illuminance using active rules within compromising the user's emotion. For this, we set the specific range of standard illuminance and the lower bound of user's emotional margin of illuminance based on measurements and analysis, and use these data in design of active rules. And then, we design and implement the active rule system using mobile agent. The mobile agent in the proposed system migrates to the destination sensor nodes, acquires and transmits sensor data according to the purpose and needs through the active rules, and directly executes the actions corresponding to the optional events(changed sensor data and/or time etc.). And then, we show the potential applicability of the proposed active rule system in various active sensor network applications through the interaction with the rule base and mobile sensor network middleware system.

• The KIPS Transactions:PartA
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• v.18A no.4
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• pp.159-164
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• 2011

In this paper, we suggest the active multi-agent middleware for the sensor network application. For this, firstly we design and implement the active rule based mobile agent middleware. The mobile agent in the proposed system visits the destination sensor nodes according to the migration list offered by the meta table in the name space of the naming agent, acquires and transmits sensor data according to the purpose and needs through the active rules, and directly executes the actions corresponding to the optional events(changed sensor data and/or time etc.). And then, we show the potential applicability of the active rule based mobile agent middleware in various active sensor networks through the interaction with the rule base system and context database system.