• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.411-416
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• 1990

A modelling process of a robotic assembly cell and a method for analysis of the assembly cell operation through simulation are presented. An assembly cell including industrial robots is the subject of the model. The states of the assembly cell elements are taken as the state variables and the relationships between the states are described mathematically using the operators. An algorithm for the cell operation is developed from the relationships between the states and the information on the assembly task, and efficient analyses are performed by the simulation results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.3
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• pp.97-101
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• 2008

In this paper, an assembly education training system is presented using AR (augmented reality). The effectiveness of the training using the proposed system is verified on a PC assembly training experiment. The experimental results confirmed the training using the proposed system is more effective than that using the conventional systems based on texts and images by reducing the assembly (task) time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.1061-1062
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• 2009

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1072-1077
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• 1992

In ths paper a new active assembly algorithm for chamferless precision parts mating, is considered. The successful assembly task requires an extremely high position accuracy and a good knowledge of mating parts. However, conventional assembly mehtod alone makes it difficult to achieve satisfactory assembly performance because of the complexity and the uncertainties of the process and its environments such as imperfect knowledge of the parts being assembled as well as the limitation of the devices performing the assebled as well as the limitation of the devices performing the assembly. To cope with these problems, a self-learning rule-based assembly algorithm is proposed by intergaring fuzzy set theory and neural network. In this algortihm, fuzzy set theory copes with the complexity and the uncertainties of the assembly process, while neural network enhances the assembly schemen so as to learn fuzzy rules form experience and adapt to changes in environment of uncertainty and imprecision. The performance of the proposed assembly algorithm is evaluated through a series of experiments. The results show that the self-learning fuzzy assembly scheme can be effecitively applied to chamferless precision parts mating.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.272-279
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• 2002

A common task in assembly modeling is the determination of the position and orientation of a set of components by solving the spatial relationships between them. Assembly models could be constructed at various levels of abstraction. They could be classified into component or geometry-level assembly models. The geometry-level assembly design approach using mating constraints such as against and fits is widely used in the commercial modelers, but it may be very tedious in some cases fur designer. In this paper, we propose a new method to construct an assembly model at the component-level by extracting joint mating features from the kinematics constraints specified between components. The assembly model constructed using the proposed method includes hierarchical and relational assembly models, component/sub-assembly positions and degrees of freedom information. The proposed method is more intuitive and natural way of assembly design and it guarantees the topological robustness of assembly modification such as component replacement and modification.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.535-546
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• 2024

This research aims to develop a model to objectively and quantitatively measure the skill level of aircraft body assembly workers. Because aircraft body assembly is predominantly a manual process, skills management is a key factor of manufacturing competitiveness. Currently, skills management relies on the subjective judgment of supervisors, which lacks objectivity and reliability. As a remedy, this study proposed a systematic skill management model based on objective and quantitative evaluation criteria. By considering prior research, we developed an evaluation model that takes into account both expertise and versatility of a worker. The model selected five major tasks required for aircraft body assembly and established evaluation criteria considering the difficulty and maturity of each task. We then conducted a pilot evaluation with over 200 workers in four SMEs to validate the practicality and effectiveness of the model. Consequently, we identified and addressed the limitations of the existing evaluation method, subdivided the skill levels based on the performance capabilities of each task, and proposed a career growth path. The developed evaluation model offers critical data for executives and managers to determine work assignments, education, training, performance incentives, and wages. It is expected to enhance the attraction of new talent and systematize skills management in aviation manufacturing in the future.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.972-976
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• 2015

The objective of this research is to verify the quantitative efficiency of a bimanual robotic task. Bimanual robots can realize dexterous and complicated motions using two cooperating arms. However, its motion planning and control method are not simple for implementing flexible tasks such as assembly. In this paper, the proposed motion planning method is used to find an optimal solution satisfying a designed cost function and constraints with regard to the kinematics and redundancy of the bimanual robot. The simulation results show that the lifetime of the manipulator can be changed by the proposed cost function consisting of angular velocity and angular acceleration of each joint in the same assembly task.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.164-171
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• 2022

Recently, interest of a dual arm robot which can replace humans is increasing in order to improve the working environment and solve the labor shortage. Various studies related with design and analysis of dual-arm robots have been conducted because dual arm robots can have various kinematic configurations according to the objective task. It is necessary to evaluate the work performance according to various kinematic structures of the dual arm robot to maximize its effectiveness. In the paper, the performance analysis is studied according to the shoulder configuration and the wrist configuration of the dual-arm robot by using main performance indices such as manipulability, condition number, and minimum singular value by assigning proper weight values to each objective motion. Performance analysis for the robotic assembly process is effectively carried out for each representative dual arm robot configuration.

• 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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.10-18
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• 1997

This paper presents the development of real-time estimation and control details for a computer vision-based robot control method. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes know 4-axis Scorbot manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method. The method is tested experimentally in two ways : First the validity of estimation model is tested by using the self-built test model. Second, the practicality of the presented control method is verified in performing 4-axis manipulator's assembly task. These results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as deburring and welding.