• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.455-462
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• 2022

Since electric connectors such as power connectors have a small assembly tolerance and have a complex shape, the assembly process is performed manually by workers. Especially, it is difficult to overcome the assembly error, and the assembly takes a long time due to the error correction process, which makes it difficult to automate the assembly task. To deal with this problem, a reinforcement learning-based assembly strategy using contact states was proposed to quickly perform the assembly process in an unstructured environment. This method learns to generate a search trajectory to quickly find a hole based on the contact state obtained from the force/torque data. It can also learn the stiffness needed to avoid excessive contact forces during assembly. To verify this proposed method, power connector assembly process was performed 200 times, and it was shown to have an assembly success rate of 100% in a translation error within ±4 mm and a rotation error within ±3.5°. Furthermore, it was verified that the assembly time was about 2.3 sec, including the search time of about 1 sec, which is faster than the previous methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1597-1606
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• 2003

Static analysis using hybrid finite element(FE) method has been applied to characterize the influence of position, runout and thickness errors of the sun, ring and planet on the bearing forces and critical tooth stress. Some guidelines for tolerance control to manage critical stress and bearing forces are deduced from the results. Carrier indexing error planet assembly and planet tooth thickness error are most critical to reduce planet bearing force and maximize load sharing as well as to reduce critical stresses. Sun and carrier bearing forces due to errors increase several times more than those of normal condition.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.461-468
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• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3863-3869
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• 2009

In recent years, globalization of markets and increased consumer sophistication in automotive industry have led to an increase in the variety of products and a consequent increase in the number of variants of any given product line that a manufacturer must supply. Also, the modularity trend of automotive production systems greatly affects on the production systems of automotive parts suppliers. These typically requires the implementation of cost efficient, flexible production systems, so called mixed-model assembly lines. We studied the problems of mixed-model assembly and assembly error-preventing techniques, and developed the error-preventing monitoring system using RFID in the mixed-model automotive parts assembly line. Especially, this study aimed to solve the problems and supplement the existing systems for preventing assembly errors, by developing a monitoring system using RFID to minimize the issues currently occurring in the field of automotive parts assembly, such as losses from incorrect installation and omission.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.24-30
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• 2021

In this study, an augmented reality (AR) app that detects the screw-assembly state of a car valve-body and assists the assembly work is developed and the effectiveness of the app is shown through testing. The app creates the contents indicating the screw-assembly position and order, and the screw-assembly state. Then, the contents are registrated onto the valve-body image on a smart-phone screen to be shown to the worker during assembly. To this end, the features are extracted from the 2D image of the valve-body and the location of the valve-body is tracked. By extracting the areas where the screws are to be assembled, and periodically determining the luminance of these areas, it is checked whether the screws are assembled in order at the predetermined position of the valve-body. When an error is detected during assembly, a warning sound is notified to the worker, and the worker can check the assembly state on the smart-phone screen and handle the error, immediately. Study results found that it takes about 65 ms to detect the assembly state of the five screws, and the assembly state is detected without error for 1 hour.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.4
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• pp.7-12
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• 2004

Inspection and analysis are essential process to determine whether a completed product is in given specification or not. Analysis of products with very complicated shape is difficult to carry out direct comparison between inspected coordinate and designed coordinates. So process called as matching or registrations is needed to solve this problem. By defining error between two coordinates and minimizing the error, registration is done. Registration consists of translation, rotation and scale transformations. Error must be defined to express feature of inspected product. In this paper, registration algorithm is developed to determine pose of sub-frame at assembly with body of automobile by defining error between two coordinates considering geometric feature of sub-frame.

• Nuclear Engineering and Technology
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• v.22 no.2
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• pp.95-100
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• 1990

The exact expression for the 1151 force on a fuel assembly in a reactor core is derived in terms of calculable hydraulic parameters. The relation for the lift force. pressure drop, buoyancy force, viscous force. and fuel assembly weight is discussed. Based on the derived exact expression. error analysis is made for a simple expression applying COBRA IV-i to a typical PWR fuel assembly. The error analysis revealed that the error of the simple expression consists of four terms and the overall error depends on the flow rate change direction, and its magnitude is about 1%.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.17-25
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• 2005

In this paper, we design data transformation interface for the automation of PCB product. The data designed to CAD does not exchange itself for the assembly line, so we construct an automation system which is exchangeable. To do this, we analyze the information of PCB components and construct the Information of IC components as database. We also develope two kinds of algorithm; one is to detect human error and another is to exchange itself for the data which is suitable for PCB assembly line. We design data transformation interface to do addition and revision of the information for PCB assembly line. By automating existing manual processing, we are able to shorten access time and enhance reliability of the data and the efficient assembly line of PCB.

• Korean Journal of Microbiology
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• v.43 no.4
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• pp.317-320
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• 2007

In this paper, we have developed base-calling error detection program and algorithm which show the list of the genes or sequences that are suspected to contain base-calling errors. Those programs detect dubious bases in a few aspects in the process of microbial genome project. The first module detects base-calling error from the Phrap file by using contig assembly information. The second module analyzes frame shift mutation if it is originated from real mutation or artifact. Finally, in the case that there is control microbial genome annotation information, the third module extracts and shows the candidate base-calling error list by comparative genome analysis method.

• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.583-598
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• 2015

We need many assembly lines to produce industrial product such as automobiles that require a lot of composited parts. Big portion of such assembly line are still operated by manual works of human. Such manual works sometimes cause critical error that may produce artifacts. Also, once the assembly is completed, it is really hard to verify whether of not the product has some error. In this paper, for monitoring behaviors of manual human work in an assembly line automatically, we proposes a realtime hybrid monitoring system that combines 2D vision sensor tracking technique with 3D motion recognition sensors.