• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.409-410
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• 2007

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.237-240
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• 2005

This paper describer a design expert system which determines the design values of shadow mask using Case-Based Reasoning. In Case-Based Reasoning, it is important to both retrieve similar cases and adapt the cases to meet the design specifications exactly. Especially, the difficulty in automating the adaptation process will prevent the designers from using the design expert systems efficiently and easily. This paper explains knowledge-based design support systems for shadow mask through neural network-based case adaptation. Specifically, we developed 1) representing design knowledge and 2) adaptive case-based reasoning method using RBFN (Radial Basis Function Network).

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.635-636
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• 2006

A knowledge-based system with CAD is widely used to implement a designer's know-how and a routine calculation within a system. An engineer needs to change several design parameters in an early design stage. However it is not easy to change the design parameters when it needs to update an existing model and data. In this paper, a module has been proposed to make it easy to change the design parameter so that the engineer can easily update and change the design model. Also a flexible interface of the module can easily add or extract the design knowledge.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.798-803
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• 2005

The increasing complexity of modem products requires the effective management of design knowledge, which partly resides in the product itself on the one hand. On the other hand, a lot of knowledge is gathered and/or generated during the design process, but disappears as the design project concludes. This paper describes a knowledge representation method to accommodate the implicit design knowledge. The method is based on the FBS(Function-Behavior-Structure) model and extends the object ontology with constraint entity. An example to represent the injection mold design knowledge is given to show its applicability.

• Journal of the Microelectronics and Packaging Society
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• v.9 no.1
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• pp.43-48
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• 2002

Semiconductor chip encapsulation process is employed to protect the chip and to achieve optimal performance of the chip. Expert decision-making to obtain the appropriate package design or process conditions with high yields and high productivity is quite difficult. In this paper, an expert system for semiconductor chip encapsulation has been constructed which combines a knowledge-based system with CAE software.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.205.1-205.1
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• 2005

• Journal of Digital Convergence
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• v.15 no.3
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• pp.313-318
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• 2017

In general, users of design software such as Photoshop, search for information online when they want to obtain related knowledge. However, it is very difficult to find the exact information they want about designs because available knowledge sharing systems are very broad in what they manage, and it is rare that such systems would provide any design-specific Q&A or exchange of information functionality. In the paper we development a video based system for sharing design knowledge that supplies Q&A, lecture, knowledge trade function etc. utilizing multimedia like text, image and video reflecting the characteristics of design knowledge. The system are expected to contribute to the competitiveness of products through sharing design knowledge. In the near future the system will need to expand to a framework that can be shared with a variety of knowledge, as well as design knowledge.

• Journal of Ship and Ocean Technology
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• v.5 no.3
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• pp.27-35
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• 2001

In this research, hybrid method with case-based reasoning and rule-based reasoning is applied. Using case-based reasoning, design experts'experience and know-how are effectively represented in order to obtain a proper configuration of midship section in the initial ship design stage. Since there is not sufficient domain knowledge available to us, traditional case-adaptation algorithms cannot be applied to our problem, i.e., creating the configuration of midship section. Thus, new case-adaptation algorithms not requiring any domain knowledge are developed antral applied to our problem. Using the knowledge representation of DnV rules, rule-based reasoning can perform deductive inference in order to obtain the scantling of midship section efficiently. The results from the case-based reasoning and the rule-based reasoning are examined by comparing the results with various conventional methods. And the reasonability of our results is verified by comparing the results wish actual values from parent ship.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.145-162
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• 1992

This paper proposes two design principles for expert systems to solve a stock market timing (SMART) problems : machine knowledge and fuzzy post-adjustment, Machine knowledge is derived from past SMART instances by using an inductive learning algorithm. A knowledge-based solution, which can be regarded as a prior SMART strategy, is then obtained on the basis of the machine knowledge. Fuzzy post-adjustment (FPA) refers to a Bayesian-like reasoning, allowing the prior SMART strategy to be revised by the fuzzy evaluation of environmental factors that might effect the SMART strategy. A prototype system, named K-SISS2 (Knowledge-based Stock Investment Support System 2), was implemented using the two design principles and tested for solving the SMART problem that is aimed at choosing the best time to buy or sell stocks. The prototype system worked very well in an actual stock investment situation, illustrating basic ideas and techniques underlying the suggested design principles.