• 지능정보연구
• /
• 제8권1호
• /
• pp.159-173
• /
• 2002

사출금형 공정계획이란 금형설계를 완료한 후에 설계된 금형을 경제적, 효율적으로 생산하기 위하여 수행하는 제조공정에 대한 계획이다. 이러한 공정계획은 전문가의 수작업에 의한 수립에 의한 문제, 전문가의 양성과 부족현상, CAD/CAM 시스템 보급 및 생산형태의 다품종소량화 현상에 의해 자동화가 필요하다. 본 연구에서는 사례기반추론(Case-Based Reasoning)을 이용하여 IIMPPS(Intelligent Injection Mold Process Planning System)라는 사출금형 공정계획시스템을 개발하였다. 사출금형 공정계획을 자동화하기 위해서 사례기반 추론을 사용한 이유는 사출금형이라는 제품은 금형의 종류와 구조 등에 따라 공정계획이 매우 다양하게 수립되지만, 성형품의 용도나 품명이 같은 경우에는 공정이 거의 유사하여, 과거에 수립된 공정계획이 새로운 금형의 공정 계획에 매우 유용하게 사용될 수 있기 때문이다. 그리고 본 연구에서는 IIMPPS의 타당성을 평가하기 위하여 전문가의 정성적인 평가와 공정계획의 정확도 평가를 수행하였다.

• 한국지능시스템학회논문지
• /
• 제11권7호
• /
• pp.584-590
• /
• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• 스마트미디어저널
• /
• 제5권4호
• /
• pp.111-115
• /
• 2016

Intelligent robots are being introduced and utilized to create new values in diverse fields such as medical care, national defense, education, and manufacturing. However, while the technical aspects of intelligent robots are spreading, the business side is lacking in recognition. The purpose of this study is to identify the factors affecting product innovation through the introduction of intelligent robots in enterprises. Among the six variables secured from the technology, organization, and environment framework, only perceived direct usefulness and competitive pressure have significant effects on product innovation. The results imply that the effects of introducing robots are still in their early stage from a business perspective.

• Journal of Information Science Theory and Practice
• /
• 제10권spc호
• /
• pp.66-75
• /
• 2022

The manufacturing industry is the foundation that drives economic growth, and manufacturing innovation is essential for sustainable growth advantage and the transition into a digital economy. Therefore, major countries actively support the field of simulations, which incorporate information and communication technologies into manufacturing, and announce various policies at the national level along with increasing investment. Simulation technology virtualizes product development processes to replace physical production and experimentation of products, dramatically reducing time and costs. In South Korea, the Korea Institute of Science and Technology Information (KISTI) has supported manufacturing companies for about 14 years by providing relevant technologies. This study uses the input-output table for the Bank of Korea to analyze the economic ripple effect. First, we identified the domestic industrial sector dealing with the supercomputing-based simulation industry. Then we analyzed its ripple effects by dividing them into the production inducement effect, value-added inducement effect, employment inducement effect, and forward/backward linkage effect. Consequently, when the supercomputing simulation budget of KISTI (28.3 billion won, 2007-2020) was set as an input coefficient, the analysis showed 45.1 billion won as the production inducement effect, 24.7 billion won as the value-added inducement effect, and 282 individuals per 1 billion won as the employment inducement effect. This study is significant in that it derived the effects of the inputs by analyzing the economic ripple effects of the projects of KISTI, which have been supporting South Korean manufacturing companies for the past 14 years with supercomputing-based simulations.

• International Journal of Control, Automation, and Systems
• /
• 제3권3호
• /
• pp.461-468
• /
• 2005

This paper proposes a wheel-assembly automation system, which assembles a wheel into a hub of a vehicle hung to a moving hanger in a car manufacturing line. A macro-micro manipulator control strategy is introduced to increase the system bandwidth and tracking accuracy to ensure insertion tolerance. A camera is equipped at the newly designed wheel gripper, which is attached at the center of the end-effector of the macro-micro manipulator and is used to measure position error of the hub of the vehicle in real time. The redundancy problem in the macro-micro manipulator is solved without complicated calculation by assigning proper functions to each part so that the macro part tracks the velocity error while the micro part regulates the fine position error. Experimental results indicate that tracking error satisfies the insertion tolerance of assembly $({\pm}1mm)$, and thus it is verified that the proposed system can be applied to the wheel assembly task on a moving hanger in the manufacturing line.

• International Journal of Precision Engineering and Manufacturing
• /
• 제7권3호
• /
• pp.18-23
• /
• 2006

The formation degree of sustain (ITO pattern) determines the quality of a PDP (Plasma Display Panel). Thus, in the present study, we attempt to detect 100% of the defects that are larger than $30{\mu}m$. Currently, the inspection method in the PDP manufacturing process is dependent upon the naked eye or a microscope in off-line mode. In this study, a prototype inspection system for PDP ITO patterned glass is developed. The developed system, which is based on a line-scan mechanism, obtains information on the defects and sorts the defects by type automatically. The developed inspection system adopts a multi-vision method using slit-beam formation for minimum inspection time and the detection algorithm is embodied in the detection ability. Characteristic defects such as pin holes, substances, and protrusions are extracted using the blob analysis method. Defects such as open, short, spots and others are distinguished by the line type inspection algorithm. It was experimentally verified that the developed inspection system can detect defects with reliability of up to 95% in about 60 seconds for the 42-inch PDP panel.

• 한국기계가공학회지
• /
• 제12권2호
• /
• pp.14-19
• /
• 2013

The size and distribution of residual stresses and the effect of the minimum mesh size were investigated by the a-Si thin film solar cell. Attributed to the difference in coefficient of thermal expansion of the a-Si and Ag concentrated residual stresses at the joint interface of dissimilar materials. The ${\sigma}y$ and ${\tau}xy$ didn't appear in the central part, but ${\sigma}x$ existed. However, ${\sigma}x$, ${\sigma}y$ and ${\tau}xy$ appeared in the edge part and concentrated residual stresses at the interface between a-Si and Ag. Minimum mesh size gets smaller, the concentration of ${\sigma}y$ was significantly and existence area was reduced. As a result, the failure of thin film solar cells during the cutting process can be explained by the residual stresses.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제9권4호
• /
• pp.249-254
• /
• 2009

The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제4권1호
• /
• pp.84-89
• /
• 2004

The machine cell formation problem is the problem to group machines into machine families and parts into part families so as to minimize bottleneck machines, exceptional parts, and inter-cell part movements in cellular manufacturing systems and flexible manufacturing systems. This paper proposes a new machine cell formation method based on the adaptive Hamming net which is a kind of neural network model. To show the applicability of the proposed method, it presents some experiment results and compares the method with other cell formation methods. From the experiments, we observed that the proposed method could produce good cells for the machine cell formation problem.

• 한국경영과학회지
• /
• 제24권2호
• /
• pp.1-15
• /
• 1999

This research involves the development and evaluation of a work flow control model for a type of flexible manufacturing system(FMS) called a flexible flow line(FFL). The control model can be considered as a kind of hybrid intelligent model in that it utilizes both computer simulation and neural network technique. Training data sets were obtained using computer simulation of typical FFL states. And these data sets were used to train the neural network model. The model can easily incorporate particular aspects of a specific FFL such as limited buffer capacity and dispatching rules used. It also dynamically adapts to system uncertainty caused by such factors as machine breakdowns. Performance of the control model is shown to be superior to the random releasing method and the Minimal Part Set(MPS) heuristic in terms of machine utilization and work-in-process inventory level.