• 조명전기설비학회논문지
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• 제26권10호
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• pp.89-94
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• 2012

This research is to apply the control of neuron networks for the real-time walking control of Multi-articulated robot. Multi-articulated robot is expressed with a complicated mathematical model on account of the mechanic, electric non-linearity which each articulation of mechanism has, and includes an unstable factor in time of walking control. If such a complex expression is included in control operation, it leads to the disadvantage that operation time is lengthened. Thus, if the rapid change of the load or the disturbance is given, it is difficult to fulfill the control of desired performance. This paper proposes a new mode to implement a neural network controller by installing a real object for controlling and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The proposed control algorithm generated control signs corresponding to the non-linearity of Multi-articulated robot, which could generate desired motion in real time.

• 전력전자학회논문지
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• 제2권4호
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• pp.45-55
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• 1997

FA의 중요성이 증가함에 따라 AGV(Autonomous Guided Vehicle)의 역할 또한 중요시되고 있다. 본 논문은 인공 지능의 여러 방법론을 통합하여 하이브리드 형태의 제어기가 가질 수 있는 상호 보완적인 특징을 이용하고자 하며, 유전자 알고리즘에 의한 자기조직이 가능한 퍼지제어기로써 능동적이고 효과적인 AGV 제어기를 구성하고자 한다. 자기 조직이 가능한 퍼지 제어기는 구성하기 위하여 GA(Genetic Algorithm)를 사용하여 멤버십 함수와 제어 규칙을 최적에 근사하게 튜닝하였으며 제어 규칙의 자기 수정 또는 생성을 통하여 제어 성능을 향상시킨다.

• 한국안전학회지
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• 제19권1호
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• pp.23-30
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• 2004

Modern production systems are very complex by request of automation, and failure modes that occur in thisautomatic system are very various and complex. The efficient fault diagnosis for these complex systems is essential for productivity loss prevention and cost saving. Traditional fault diagnostic system which perforns sequential fault diagnosis can cause catastrophic failure during diagnosis when fault propagation is very fast. This paper describes the Real-time Intelligent Multiple Fault Diagnosis System (RIMFDS). RIMFDS assesses current machine condition by using sensor signals. This system deals with multiple fault diagnosis, comprising of two main parts. One is a personal computer for remote signal generation and transmission and the other is a host system for multiple fault diagnosis. The signal generator generates various faulty signals and image information and sends them to the host. The host has various modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault diagnosis and graphic representation of the results. RIMFDS diagnoses multiple faults with fast fault propagation and complex physical phenomenon. The new system based on multiprocessing diagnoses by using Hierarchical Artificial Neural Network (HANN).

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2005년도 춘계학술대회 논문집
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• pp.415-418
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• 2005

In recent years, Magnesium (Mg) and its alloys have become a center of special interest in the automotive industry. Due to their high specific mechanical properties, they offer a significant weight saving potential in modem vehicle constructions. Most Mg alloys show very good machinability and processability, and even the most complicated die casting parts can be easily produced. The die casting process is a fast production method capable of a high degree of automation for which certain Mg alloys are ideally suited. Although Mg alloys are fulfilling the demands for low specific weight materials with excellent machining and casting abilities, they are still not used in die casting process to the same extent as the competing material aluminium. One of the reasons is that effects of various forming variables for die casting process is not closely examined from the viewpoint of die design. In this study, step die and flowability tests for AM60 were performed by die casting process according to various combination of casting pressure and plunger velocity. Microstructure and Victors hardness tests were examined and performed for each specimen to verify effects of forming conditions.

• 한국정밀공학회지
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• 제17권8호
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• pp.106-112
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• 2000

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skiful engineers. grinding operations include a large number of functional parameters since there are several ways of coping with ginding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workshop the other is the quantitative method which utilizes the experimental data obtained by sensor. But they are all difficult to accomplish from the grinding trouble-shooting system The reason is that grinding troubles are not accomplish from the grinding trouble-shooting system,. The rason is that grinding troubles are not easily controlled in the quantitative method and therefore trouble-shooting has mainly relied on the knoledge of skiful engineers. Thus there is an important issue of how a grinding touble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper basic strategy to develop the grinding database by taking rule-based model which is strongly depended upon experience and intuition is described.

• 열처리공학회지
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• 제31권2호
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• pp.63-67
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• 2018

Recent mold industry uses many roll-to-roll processes that can produce high production speed and precision machining and automation process. In the circular cylinder mold, however, patterns of less than $10{\mu}m$ are difficult to manufacture and maintain. In this study, we fabricated a circular cylindrical mold with a DLC thin film which have high hardness, low coefficient of friction and high releasability by using lithography and lift-off process. The height, line width, and pitch of the fabricated DLC macro pattern are $3.1{\mu}m$, $9.1{\mu}m$ and $20.2{\mu}m$, respectively. The pattern size is finer than the current applied to the aluminum cylinder type, and this shows the possibility of practical use of DLC micro pattern roll mold.

• 한국BIM학회 논문집
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• 제9권3호
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• pp.8-18
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• 2019

Precast concrete manufacturing has proved economies of scale through the repetitive production by means of standardization, automation, and prefabrication. Advanced digital design and fabrication technologies can empower its benefits by enabling mass customization in the building design and construction. This study analyzed five case studies in terms of 1) design intent and background, 2) module development and facade construction, 3) integrated process among project stakeholder. This article has attempted to establish the following three points in conclusion: 1) Form generating digital design tools such as Rhino, CATIA, Generative Component, and Digital Project were implemented to produce parametric surface pattern and rationalization to maximize existing precast manufacturing benefits. Also, BIM program has been used to promote coordination and communication among engineering consultants and contractors, 2) In addition to traditional precast concrete materials, GFRC, RFP, brick cladding precast and 3D printed mould have been introduced to reduce the weight and cost and to comply the code from the zoning, seismic, and fireproof requirements, 3) Design-assist contract, design-assist financial support, and co-location measures have been introduced to facilitate collaboration between architect, fabricator, and contractor from the beginning of the project.

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.103-109
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• 2018

This paper presents an idea and framework to automate a full cycle business process management and re-engineering by integrating traditional business process management systems, process mining, data mining, machine learning, and simulation. We build our framework on the cloud-based platform such that various data sources can be incorporated. We design our systems to be extensible so that not only beneficial for practitioners of BPM, but also for researchers. Our framework can be used as a test bed for researchers without the complication of system integration. The automation of redesigning phase and selecting a baseline process model for deployment are the two main contributions of this study. In the redesigning phase, we deal with both the analysis of the existing process model and what-if analysis on how to improve the process at the same time, Additionally, improving a business process can be applied in a case by case basis that needs a lot of trial and error and huge data. In selecting the baseline process model, we need to compare many probable routes of business execution and calculate the most efficient one in respect to production cost and execution time. We also discuss the challenges and limitation of the framework, including the systems adoptability, technical difficulties and human factors.

• Smart Structures and Systems
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• 제24권3호
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• pp.403-414
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• 2019

Offshore drilling has become a key process for obtaining oil. Offshore platforms have many applications, including oil exploration and production, navigation, ship loading and unloading, and bridge and causeway support. However, vibration problems caused by severe environmental loads, such as ice, wave, wind, and seismic loads, threaten the functionality of platform facilities and the comfort of workers. These concerns may result in piping failures, unsatisfactory equipment reliability, and safety concerns. Therefore, the vibration control of offshore platforms is essential for assuring structural safety, equipment functionality, and human comfort. In this study, an optimal multiple tuned mass damper (MTMD) system was proposed to mitigate the excessive vibration of a three-dimensional offshore platform under ice and earthquake loadings. The MTMD system was designed to control the first few dominant coupled modes. The optimal placement and system parameters of the MTMD are determined based on controlled modal properties. Numerical simulation results show that the proposed MTMD system can effectively reduce the displacement and acceleration responses of the offshore platform, thus improving safety and serviceability. Moreover, this study proposes an optimal design procedure for the MTMD system to determine the optimal location, moving direction, and system parameters of each unit of the tuned mass damper.

• 대한안전경영과학회지
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• 제22권1호
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• pp.9-14
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• 2020

Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.