• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.391-398
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• 1998

Effective use of agricultural informations is crucial for 21 century farming. An interactive agricultural machinery information system was developed. It consisted of databases, knowledge bases, expert systems, a server engine, clients for a multimedia agricultural machinery information system based on Java and distributed objects technology. It is supposed to be served through a nationwide super information communication network for my farmers to utilize it interactively and quickly. Several user-friendly interface programs for users were developed to use texts, static k dynamic images, and expert systems easily. Tools for providing the informations were built with JAVA. Information providers permitted to access to the system such as agricultural machinery companies can easily add or modify the informations using distributed object technology. This system can interact among three groups : prime information provider (or system manager), permitted information providers, and farmers.

• IE interfaces
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• v.6 no.2
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• pp.19-35
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• 1993

This paper presents the development of a knowledge-based expert system to assist for designer in the process of designing products for easier assembly. The developed expert system for supporting assembly-oriented product design, which is named as DFA-MASTER, consists of two subsystems such as "Assembly Method Selection System" which provides feasible assembly methods to designer and "DFA-Analysis System" which provides guidelines to improve assemblability of products in the early stage of product design. The developed system is interfaced with AutoCAD system and can be run under PC environments. By using DFA-MASTER, designer can obtain feasible assembly methods which have high assemblability under the given asssembly conditions and also evaluate the assemblability of part feature or product structure.

• Journal of the Korean Society of Safety
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• v.7 no.2
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• pp.14-23
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• 1992

A methodology for developing an object description system based on functional-structure of chemical plant is proposed. A knowledge base for chemical plant fault diagnosis is also organized in a generic fashion using the heuristic knowledge of human operators. 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. A computer-based system based on thls methodology and knowledge base has been developed and applied to the subprocess of ethylene plant to evaluate the effectiveness of the methodology.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1254-1263
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• 1993

Representing knowledge uncertainty , aggregating evidence confidences , and propagation uncertainties are three key elements that effect the ability of a rule-based expert system to represent domains with uncertainty . Fuzzy set theory provide a good mathematical tool for representing the vagueness associated with a variable when , as the condition of a rule , it only partially corresponds to the input data. However, the aggregation of ANDed and Ored confidences is not as simple as the intersection and union operators defined for fuzzy set membership. There is, in fact, a certain degree of compensation that occurs when an expert aggregates confidences associated with compound evidence . Further, expert often consider individual evidences to be varying importance , or weight , in their support for a conclusion. This paper presents a flexible approach for evaluating evidence and conclusion confidences. Evidences may be represented as fuzzy or nonfuzzy variables with as associat d degree of certainty . different weight can also be associated degree of certainty. Different weights can also be assigned to the individual condition in determining the confidence of compound evidence . Conclusion confidence is calculated using a modified approach combining the evidence confidence and a rule strength. The techniques developed offer a flexible framework for representing knowledge and propagating uncertainties. This framework has the potention to reflect human aggregation of uncertain information more accurately than simple minimum and maximum operator do.

• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.1079-1087
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• 2003

A lot of expert systems have been developed in the area of medical diagnosis and prescription, but there has been relatively little effort to develop medical expert systems using domestic technologies. In this paper, a medical expert system for gastroenteritis is developed, which can be easily used on the Internet. This system is implemented using Java technologies and Jess, which is a Java expert system shell. Therefore. the system can be used independently from a specific platform on the Internet. In addition, facts and rules of a knowledge base in the system ate represented separately making the system updatable and expandable with ease.

• Computers and Concrete
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• v.14 no.6
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• Korean Journal of Cognitive Science
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• v.15 no.4
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• pp.15-20
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• 2004

To develop a cognitive system with the flexibility and breadth of human, it's very important to construct a large scale knowledge base which include commonsense knowledge as well as expert knowledge. Efficient knowledge representation and reasoning techniques will play a key role for this. This paper introduce a cognitive system which is based on Cyc knowledge base and augmented with our work on qualitative and spatial representation and reasoning. Our system has been implemented and tested on various examples.

• IE interfaces
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• v.11 no.2
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• pp.159-176
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• 1998

In the motor manufacturing system with the properties of short delivery and order based production, the process plan is performed individually for each order by the expert of process plan after the completion of the detail design process to satisfy the specification to be required by customer. Also it is hard to establish the standard process plan in reality because part routings and operation times are varied for each order. Hence, the production planner has the problem that is hard to establish the production schedule releasing the job to the factory because there occurs the big difference between the real time to be completed the process plan and the time to be required by the production planner. In this paper, we study the decision supporting system for the process plan based on knowledge base concept. First, we represent the knowledge of process planner as a database model through the modified POI-Feature graph. Then we design and implement the decision supporting system imbedded in the heuristic algorithm in the client/server environment using the ORACLE relational database management system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.323-331
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• 1995

The role of equipment maintenance in manufacturing becomes important. As a method of overcoming this problems, diagnostic expert system has been introduced. If such a system is, however, based on the troubleshooter's knowledge, many difficult cases are occured in the real process of diagnosis using that kind of system. This paper suggests to use the designer's knowledge for diagnosing the malfunctions of production equipments. To do that, a method of knowledge represen-tation is also proposed, which is based on the concept of boundary factors. In addition, the disorder propagation in considered. As a results, one can simplify the process of reasoning and inspection.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.