• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.04a
• /
• pp.182-187
• /
• 2000

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for similar model of fifth cell among the twelve cell for automatic test and assemblig in S company.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.15 no.2
• /
• pp.24-29
• /
• 2006

The use electron-beam(E-beam) manufacturing system provides a means to alleviate optic exposure equipment's problems. We are developing an E-beam manufacturing system with scanning electron microscope(SEM) function. The E-beam manufacturing system consist of high voltage generator, beam blanker, condenser lenses, object lenses, stigmator and stage. The development of E-beam manufacturing system is used on the method of remaking SEM's structure. The functions of SEM are developed. It is important for the test of E-beam performance. In E-beam manufacturing system and SEM, beam focus is important function. In this paper, we propose intelligent remote control function for beam focus in E-beam manufacturing system. The function extends the user's function and gives convenience.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.10a
• /
• pp.96-101
• /
• 2000

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.408-411
• /
• 2006

Currently, the nano economy threatens the mass economy. This is based on the internet business models. In the nano business models based on internet, the diversely personalized services are needed. Many researches of the personalization on the web have been studied. The web usage mining using click stream data is a tool for personalization model. In this paper, we propose an internet business model using evolutionary support vector machine and web response survey as a web usage mining. After analyzing click stream data for web usage mining, a personalized service model is constructed in our work. Also, using an approach of web response survey, we improve the performance of the customers' satisfaction. From the experimental results, we verify the performance of proposed model using two data sets from KDD Cup 2000 and our web server.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.244-249
• /
• 1997

Internal and external heat sources will cause to deform to machine elements in the contact joint of structure,which results in the change of contact pressure distribution different from initial assembly. Heat induced variations of contact pressure will change the static and dynamic properties such as contact stiffness,damping as well as contact heat conduction in the structure. In order to design and control the intelligent machine tool operating in variant conditions more sophisticatedly, the good prediction for the changes of prescribed propeties are strongly required especially in the contact elements adjacent to the rotational or linear bearing This paper presents some computational and experimental results in regard to static and dynamic characteristics of the press-fitted bush and shaft assembly which is a model of the bearing innerrace and shaft assembly. In the condition of heat generation on the outer surface of the bush,the effects of changes in the negative clearance and the heat flux on pressure distribution and dynamic properties are investigated. Results of this study show that the edge effect of the bush and the initial clearance have effects on the transient dynamic characteristics significantiy.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.10a
• /
• pp.446-449
• /
• 2002

Recently, advanced manufacturing system with high speed and intelligent have been developed for the betterment of machining ability. In this case, reliability prediction work with motion characteristic evaluation of sliding cover has also important roll from design procedure to manufacturing and assembly process. Accordingly in this study, H/W test -bed system for reliability evaluation of sliding cover has been developed to obtain proper reference data for design of new model, and also prevention trouble, quality and life cycle improvement extremely for advanced mother machinary.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.39 no.3
• /
• pp.83-89
• /
• 2016

The group formation problem of the machine and part is a critical issue in the planning stage of cellular manufacturing systems. The machine-part grouping with alternative process plans means to form machine-part groupings in which a part may be processed not only by a specific process but by many alternative processes. For this problem, this study presents an algorithm based on self organizing neural networks, so called SOM (Self Organizing feature Map). The SOM, a special type of neural networks is an intelligent tool for grouping machines and parts in group formation problem of the machine and part. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. In the proposed algorithm, output layer in SOM network had been set as one-dimensional structure and the number of output node has been set sufficiently large in order to spread out the input vectors in the order of similarity. In the first stage of the proposed algorithm, SOM has been applied twice to form an initial machine-process group. In the second stage, grouping efficacy is considered to transform the initial machine-process group into a final machine-process group and a final machine-part group. The proposed algorithm was tested on well-known machine-part grouping problems with alternative process plans. The results of this computational study demonstrate the superiority of the proposed algorithm. The proposed algorithm can be easily applied to the group formation problem compared to other meta-heuristic based algorithms. In addition, it can be used to solve large-scale group formation problems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.04a
• /
• pp.398-403
• /
• 2004

The demand of high speed machining is increasing because the high speed cutting providers high efficiency of process, short process time, improved metal removal capacity and better surface finish. Active magnetic bearings allow much high surface speed than conventional ball bearings and therefore greatly suitable for high speed cutting. The automatic control concept of magnetic bearing system provides ability of intelligent control of spindle system to increase accuracy and flexibility by means of adaptive vibration control. This paper describes a design and development of a milling spindle system which includes built-in motor with power 5.5㎾ and maximum speed 70,000rpm, HSK-32C tool holer and active magnetic bearing system. Magnetic actuators are designed for satisfying static load condition. The Performances of manufactured spindle system was examined for its static and dynamic stiffness, load capacity, and rotational accuracy. This spindle was run up to 70,000 rpm stably, which is 3.5 million DmN.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.10a
• /
• pp.439-444
• /
• 2004

A new efficient intelligent machining strategy named the Steepest Directed Tree method is presented in this study, which makes surface model discrete with triangulation meshes and the cutter paths track along the tree directions. In order to formulate these algorithms practically, it is deduced the multi-stage machining approach of uncut volume caused by cutter gouging in the course of milling using flat end mill. It is systematized the checking process the cutter interference by grouping the 6 kinds of gouging types, which yields the environment of connectivity data lists including CL-data, and then the multi-stage machining strategy, that minimizes uncut area by continuously sequencing the generative subsequent CL-paths, is shamed to determine the second tool path for the next uncut area and to compose the operating multi-stage cutting processes. The completed machining system of curved surfaces is evaluated by testing the practical machining experiments which have various kinds of shape conditions.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.3
• /
• pp.478-489
• /
• 2013

The controllability and stability of power systems can be increased by Flexible AC Transmission Devices (FACTs). One of the FACTs devices is Interline Power-Flow Controller (IPFC) by which the voltage stability, dynamic stability and transient stability of power systems can be improved. In the present paper, the convenient operation and control of IPFC for transient stability improvement are considered. Considering that the system's Lyapunov energy function is a relevant tool to study the stability affair. IPFC energy function optimization has been used in order to access the maximum of transient stability margin. In order to control IPFC, a Brain Emotional Learning Based Intelligent Controller (BELBIC) and PI controller have been used. The utilization of the new controller is based on the emotion-processing mechanism in the brain and is essentially an action selection, which is based on sensory inputs and emotional cues. This intelligent control is based on the limbic system of the mammalian brain. Simulation confirms the ability of BELBIC controller compared with conventional PI controller. The designing results have been studied by the simulation of a single-machine system with infinite bus (SMIB) and another standard 9-buses system (Anderson and Fouad, 1977).