• Journal of Ship and Ocean Technology
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• 제9권3호
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• pp.33-42
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• 2005

As the networks connect the world, enterprises tend to move manufacturing activities into virtual spaces. Since different software applications use different data terminology, it becomes a problem to interoperate, interchange, and manage electronic data among heterogeneous systems. It is said that approximately one billion dollar has been being spent yearly in USA for product data exchange and interoperability. As commercial CAD systems have brought in the concept of design feature for the sake of interoperability, terminologies of design features need to be harmonized. In order to define design feature terminology for integration, knowledge about feature definitions of different CAD systems should be considered. STEP standard have attempted to solve this problem, but it defines only syntactic data representation so that semantic data integration is not possible. This paper proposes a methodology for integrating modeling features of CAD systems. We utilize the ontology concept to build a data model of design features which can be a semantic standard of feature definitions of CAD systems. Using feature ontology, we implement an integrated virtual database and a simple system which searches and edits design features in a semantic way.

• 경영정보학연구
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• 제17권1호
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• pp.19-47
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• 2015

본 연구의 목적은 병원 헬스케어 서비스 분야에서 ICT 조직기능 연관성(Information and Communication Technology Relatedness)과 조직환경이 의료진간 또는 의료진과 환자간 상호작용과 지식공유에 어떻게 영향을 미치며, 지식공유는 의료 서비스 혁신, 그리고 서비스 혁신은 서비스성과에 어떻게 영향을 미치는지를 구조화된 모델을 통해 연구하는 것이다. 자원준거관점(Resource based view), 적합구조화이론(Adaptive Structuration Theory), 그리고 서비스 혁신이론을 기반으로 헬스케어 서비스 시스템에서 성과에 영향을 미치는 주요요인으로 ICT 조직기능 연관성, 구성원간의 상호작용과 지식공유를 설정했고, 성과요인으로는 서비스 혁신과 서비스 성과를 설정였다. 모델의 검증을 위해 병원에서 종사하는 의료직, 기능직, 사무직 종사자들을 대상으로 설문을 실시하여 분석하였다. 모델 검증 결과, 모든 가설들은 유의미하게 성과창출에 긍정적인 영향을 주는 것으로 밝혀졌다. 구조화된 조직환경과 ICT 조직기능 연관성은 서비스 조직구성원 및 환자들의 행위에 영향을 주어 상호작용 및 지식공유를 촉진하고, 병원 헬스케어 서비스의 혁신과 성과에 영향을 미치는 중요한 요소임을 시사하고 있다.

• 산업경영시스템학회지
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• 제27권1호
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• pp.24-31
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• 2004

With Zohar(1980)'s research on safety climate and industrial safety, occupational safety and health literatures begin to emphasize the influence of organizational context. Based on this research trend, this paper tried to review the relationship between individual/ organizational factors and occupational accidents. Based on the responses from 643 manufacturing workers, this paper reviewed the relationship between antecedents(safety knowledge, safety motivation, safety education, and safety precaution activity) and safety consequences(accident parts, accident number, resting days). The results of statistical analysis showed that many antecedents have significantly negative relationships with safety consequences.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.168.1-168
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• 2001

This article describes a novel model-based compensating neural network (NN) model developed to be used in our active binocular head controller, which addresses both the kinematics and dynamics aspects in trying to precisely track a moving object of interest to keep it in view. The compensating NN model is constructed using two classes of self-tuning neural models: namely Neural Gas (NG) algorithm and SoftMax function networks. The resultant servo controller is shown to be able to handle the tracking problem with a minimum knowledge of the dynamic aspects of the system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.7-11
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• 1991

The adaptive control of flexible joint manipulator is the focus of this paper. The full order flexible joint manipulator dynamic system does not allow the determination of a feedback linearization control as for rigid manipulators. This drawback is overcome by a model order reduction based on a singular perturbation strategy. The full order flexible joint manipulator dynamic model is adopted for derivation of the adaptive control law to damp out the elastic oscillations at the joints. It is shown that the joint position error will converge to zero asymptotically and that other signals remain bounded without precise knowledge of parameters of the manipulator and its joint flexibility.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.797-800
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• 1992

Much experience and knowledge is needed in welding because there are many working parameters and quantitative description is difficult. Therefore, introduction of expert system based on such data base has been required. In this study, welding heat and shape of bead was controlled by fuzzy inference with the welding condition, position error and voltage and current error of robot. For this, torch trajectory of robot was generated by modeling the working data with CAD and then welding was carried out through down loading to robot. And working error was controlled by on-line communication.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.131-134
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• 1990

A back-propagation neural network based system for a fault diagnosis of a chemical process is developed. Training data are acquired from FCD(Fault-Consequence Digraph) model. To improve the resolution of a diagnosis, the system is decomposed into 6 subsystems and the training data are composed of 0, 1 and intermediate values. The feasibility of this approach is tested through case studies in a real plant, a naphtha furnace, which has been used to develop a knowledge based expert system, OASYS (Operation Aiding expert SYStem).

• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• Transactions on Control, Automation and Systems Engineering
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• 제4권1호
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• pp.100-107
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• 2002

The advanced bilateral control algorithm, which can enlarge a reflected force by combining force reflection and compliance control, greatly enhances workability in teleoperation. In this scheme the maximum boundaries of a compliance controller and a force reflection gain guaranteeing stability and good task performance greatly depend upon characteristics of a slave arm, a master arm, and an environment. These characteristics, however, are generally unknown in teleoperation. It is, therefore, very difficult to determine such maximum boundary of the gain. The paper presented a novel method for design of an advanced bilateral controller. The factors affecting task performance and stability in the advanced bilateral controller were analyzed and a design guideline was presented. The neurofuzzy compliance model (NFCM)-based bilateral control proposed herein is an algorithm designed to automatically determine the suitable compliance for a given task or environment. The NFCM, composed of a fuzzy logic controller (FLC) and a rule-learning mechanism, is used as a compliance controller. The FLC generates compliant motions according to contact forces. The rule-learning mechanism, which is based upon the reinforcement learning algorithm, trains the rule-base of the FLC until the given task is done successfully. Since the scheme allows the use of large force reflection gain, it can assure good task performance. Moreover, the scheme does not require any priori knowledge on a slave arm dynamics, a slave arm controller and an environment, and thus, it can be easily applied to the control of any telerobot systems. Through a series of experiments effectiveness of the proposed algorithm has been verified.

• 시스템엔지니어링학술지
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• 제14권1호
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• pp.28-35
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• 2018

Front End Engineering Design (FEED), currently dominated by a few advanced countries, creates the highest added-value in the in plant construction industry. In the domestic plant engineering industry, it is difficult to acquire its own technology capability and experience due to lack of experience and shortage of experts in advanced design fields such as basic design and FEED. To achieve competitiveness with the advanced countries, it is necessary to establish smart training system for advanced plant design and FEED engineers. This study aims to design an integrated training framework for plant engineering and FEED using system engineering to build a smart plant engineering education system that learns design knowledge based on educational content and experience based on design stage for chemical plant.