• International Journal of Quality Innovation
• /
• v.8 no.2
• /
• pp.132-146
• /
• 2007

Constructing an effective production control policy is the most important issue in wafer fabrication factories. Most of researches focus on the input regulations of wafer fabrication. Although many of these policies have been proven to be effective for wafer fabrication manufacturing, in practical, there is a need to help operators decide which lots should be pulled in the right time and to develop a systematic way to alleviate the long queues at the bottleneck workstation. The purpose of this study is to construct a photolithography workstation dispatching rule (PADR). This dispatching rule considers several characteristics of wafer fabrication and influential factors. Then utilize the weights and threshold values to design a hierarchical priority rule. A simulation model is also constructed to demonstrate the effect of the PADR dispatching rule. The PADR performs better in throughput, yield rate, and mean cycle time than FIFO (First-In-First-Out) and SPT (Shortest Process Time).

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.6
• /
• pp.20-27
• /
• 1993

The white-balance system for color tevision is characterized by 5 input-5 output nonlinear process. A design strategy of fuzzy control rules is treated in which it can be adopted to the white balance adjustment for color television. A fuzzy rule based on an expert's knowledge is constructed, and then a multivariable fuzzy control rule is designed. Since human has just two hands, he can manipulate two variables simutaneously. In case when the process to be controlled has more than three control variables, expert's control rule is much different from the multivariable control rule. A multivariable fuzzy control rule is constructed by utilizing the expert' knowledge and rough relations between input and output variables, and its usefulness is shown by experiments.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.10
• /
• pp.25-33
• /
• 2012

In this paper, we propose a rule-based model to correct errors in a speech recognition result in the mobile device environment. The proposed model considers the mobile device environment with limited resources such as processing time and memory, as follows. In order to minimize the error correction processing time, the proposed model removes some processing steps such as morphological analysis and the composition and decomposition of syllable. Also, the proposed model utilizes the longest match rule selection method to generate one error correction candidate per point, assumed that an error occurs. For the purpose of deploying memory resource, the proposed model uses neither the Eojeol dictionary nor the morphological analyzer, and stores a combined rule list without any classification. Considering the modification and maintenance of the proposed model, the error correction rules are automatically extracted from a training corpus. Experimental results show that the proposed model improves 5.27% on the precision and 5.60% on the recall based on Eojoel unit for the speech recognition result.

• Journal of Intelligence and Information Systems
• /
• v.12 no.2
• /
• pp.67-81
• /
• 2006

While the existing Web focuses on the interface with human users based on HTML, the next generation Web will focus on the interaction among software agents by using XML and XML-based standards and technologies. The inference engine, which will serve as brains of software agents in the next generation Web, should thoroughly understand the Semantic Web, the standard language of the next generation Web. As abasis for the service, the W3C (World Wide Web Consortium) has recommended SWRL (Semantic Web Rule Language) which had been made by compounding OWL (Web Ontology Language) and RuleML (Rule Markup Language). In this research, we develop a backward chaining inference engine SMART-B (SeMantic web Agent Reasoning Tools -Backward chaining inference engine), which uses SWRL and OWL to represent rules and facts respectively. We analyze the requirements for the SWRL-based backward chaining inference and design analgorithm for the backward chaining inference which reflects the traditional backward chaining inference algorithm and the requirements of the next generation Semantic Web. We also implement the backward chaining inference engine and the administrative tools for fact and rule bases into Java components to insure the independence and portability among different platforms under the environment of Ubiquitous Computing.

• Journal of Power System Engineering
• /
• v.11 no.2
• /
• pp.51-57
• /
• 2007

As a shot sleeve in die casting plays a critical role in delivering molten metal to a die cavity, any disruption to its function in the injection stage results in deterioration of the quality of final castings. To guarantee a smooth operation of a shot sleeve, its structural stability should be maintained. Despite the simple geometry, design of shot sleeve is based on individual engineer's experience and no agreement on the design is present. In this study, we newly propose a systematic methodology to determine a minimum wall thickness of a shot sleeve to prevent yielding or plastic deformation. Analytical calculations incorporating numerical analysis produce a rational design rule for minimum thickness of a shot sleeve subject to metal intensification pressure and geometric die constraint. To validate the proposed design guideline, authors present real data on a collection of actual shot sleeves. Upon checking their conformity to the new design rule, we discovered a strong correlation between the design of wall thickness and premature failures.

• Korean Institute of Interior Design Journal
• /
• v.24 no.3
• /
• pp.30-37
• /
• 2015

The target of design is a harmony between Beauty and Usefulness. Design is a result from representation of visual language by designer's creative thinking system. also, As an ill-defined problem cannot be described completely. and subjectively interpret depend on the situation, it is very difficult to present a theoretical standard. There have been many Design Sciences researches in recent years. such as Rule Based Design, Parametric Design, Replacement Design, Analogy Design, Metaphor Design, Genetic Algorithm. but Objective research is still unsatisfactory condition to investigate true nature about Design. At this point, It is very important to formulating about meaning of Design Language and Thinking. This study will define about that, and based on this definition, Lay out a logical basis for Treatment design variable and materialization of process by "Elements", "Relationship", "Schema". ultimately it look forward to provide a framework and minimize the complexity about Design Thinking.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.1
• /
• pp.101-110
• /
• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.701-706
• /
• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• Journal of the Society of Naval Architects of Korea
• /
• v.30 no.2
• /
• pp.30-36
• /
• 1993

An expert system to help a novice engineer in designing midship section is developed. The system is developed based on a general-purpose expert system shell, NEXPERT. Firstly, the design knowledge is extracted from an existing rule scantling program. The knowledge has been grouped and structured into a hierarchy by applying object-oriented concepts. Secondly, the knowledge base is integrated with a database of existing ships and engineering analysis modules through the Application Programming Interface(API)technique. Graphical User Interface which is developed using Motif wiget set is adopted. These altogether enable construction of an user friendly expert system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.05a
• /
• pp.81-86
• /
• 2002

In current CBR(Case-Based Reasoning) systems, the case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck similar to those found in traditional expert system design. In this thesis, 1 present a model for learning method of case adaptation knowledge using case base. The feature difference of each pair of cases are noted and become the antecedent part of an adaptation rule, the differences between the solutions in the compared cases become the consequent part of the rule. However, the number of rules that can possibly be discovered using a learning algorithm is enormous. The first method for finding cases to compare uses a syntactic measure of the distance between cases. The threshold fur identification of candidates for comparison is fixed th the maximum number of differences between the target and retrived case from all retrievals. The second method is to use similarity metric since the threshold method may not be an accurate measure. I suggest the elimination method of duplicate rules. In the elimination process, a confidence value is assigned to each rule based on its frequency. The learned adaptation rules is applied in riven target Problem. The basic. process involves search for all rules that handle at least one difference followed by a combination process in which complete solutions are built.