• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.5
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• pp.259-266
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• 2022

In this study, we developed a deep learning and vision sensor-based assembly performance evaluation method isfor prefabricated steel structures. The assembly parts were segmented using a modified version of the receptive field block convolution module inspired by the eccentric function of the human visual system. The quality of the assembly was evaluated by detecting the bolt holes in the segmented assembly part and calculating the bolt hole positions. To validate the performance of the evaluation, models of standard and defective assembly parts were produced using a 3D printer. The assembly part segmentation network was trained based on the 3D model images captured from a vision sensor. The sbolt hole positions in the segmented assembly image were calculated using image processing techniques, and the assembly performance evaluation using the k-nearest neighbor algorithm was verified. The experimental results show that the assembly parts were segmented with high precision, and the assembly performance based on the positions of the bolt holes in the detected assembly part was evaluated with a classification error of less than 5%.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.95-102
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• 2001

The design of automobile body assembly line is one of essential parts for improving the process performance. The major objective of this research is to develop a performance evaluation model for automobile assembly line using a closed queueing network(CQN) and simulation method. In this study we used a two-step approach to compute the performance of the assembly line : first, we used CQN model considering assembly line equipments and the line operating time under the assumption of no failure, and second we used a well-known simulator FACTOR/AIM. Finally we implemented this model on a K automobile company and we have shown the sample results of automobile body assembly line.

• Smart Structures and Systems
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• v.32 no.2
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• pp.111-121
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• 2023

This study proposes an automated assembly performance evaluation method for prefabricated steel structures (PSSs) using machine learning methods. Assembly component images were segmented using a modified version of the receptive field pyramid. By factorizing channel modulation and the receptive field exploration layers of the convolution pyramid, highly accurate segmentation results were obtained. After completing segmentation, the positions of the bolt holes were calculated using various image processing techniques, such as fuzzy-based edge detection, Hough's line detection, and image perspective transformation. By calculating the distance ratio between bolt holes, the assembly performance of the PSS was estimated using the k-nearest neighbors (kNN) algorithm. The effectiveness of the proposed framework was validated using a 3D PSS printing model and a field test. The results indicated that this approach could recognize assembly components with an intersection over union (IoU) of 95% and evaluate assembly performance with an error of less than 5%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1191-1194
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• 2003

At present, the fabrication of optical filter for optical communication mostly depends on handwork, and only a few companies are propelling semi-automatic systems compounded with automatic and hand-operated methods. The measurement evaluation of optical filters is not commonly useful, so it causes difficulties in the producing field. And the packaging process becomes a very unstable process because the filters are judged from the results that they are not measured and immediately packaged during that process. In this situation, the automatic assembly system of optical filter for communication is extremely important and has begun to make its appearance as the most necessary technology for developing optical communication component with high-functionality. In this paper, we constructed systems of assembly and performance evaluation for micro optical collimator. And by using that, we designed a system capable of performance evaluation and assembly of film filter of about 30 $\mu\textrm{m}$ thickness as well as optical filter for common communication.

• 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 the Ergonomics Society of Korea
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• v.25 no.3
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• pp.61-66
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• 2006

Awkward work postures in workshop highly affect on work-related musculoskeletal disorders(WMSDs). Especially, in automobiles assembly process, these awkward work postures of workers may cause serious injury and illness. This study is to compare the performance among the evaluation tools which can measure the work-loads caused by the awkward work postures in automobiles assemble process. RULA, REBA and TVAL(Toyota Verification of Assembly Line) are used as the evaluation tools. The 85 jobs selected in the automobiles assembly process are applied to the three tools and their performances are analyzed after the evaluation of the work-load in each job. Through various measures of performance such as statistical test, DUNCAN test, regression test etc., the tendencies and characteristics among them are analyzed in detail.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.303-303
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• 2004

• Journal of the Korea Safety Management & Science
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• v.4 no.2
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• pp.83-101
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• 2002

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.

• Current Optics and Photonics
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• v.7 no.4
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• pp.398-407
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• 2023

We explored a method to evaluate imaging performance for the optimal assembly of an endoscopic miniature lens and a sensor constituting an imaging module at the distal end of gastrointestinal endoscopy. For the assembly of the imaging module, the image sensor was precisely located at the focal plane when collimated light passed through the endoscopic lens. As another method, the distance between the lens and sensor was adjusted to obtain the highest focus index from images measured the star chart of the International Organization for Standardization (ISO) standard at various positions. We analyzed the slanted-edge modulation transfer function (MTF), corresponding depth of field, and number of line pairs for MTF 50% and 20% at each working distance within the range of 5-100 mm for imaging modules assembled in different ways. Assembly conditions of the imaging module with better MTF performance were defined for each working distance range of 5-30 mm and 30-100 mm, respectively. In addition to the MTF performance, the focus index of each assembled module was also compared. In summary, we examined the performance of imaging modules assembled with different methods within the suggested working distance and tried to establish the optimal assembly protocol.

• Proceedings of the Safety Management and Science Conference
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• 2002.05a
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• pp.91-97
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• 2002

In this thesis presents line balancing problems of two-sided and mixed model assembly line widely used in practical fields using genetic algorithm for reducing throughput time, cost of tools and fixtures and improving flexibility of assembly lines. Two-sided and mixed model assembly line is a special type of production line where variety of product similar in product characteristics are assembled in both sides. This thesis proposes the genetic algorithm adequate to each step in tow-sided and mixed model assembly line with suitable presentation, individual, evaluation function, selection and genetic parameter. To confirm proposed genetic algorithm, we apply to increase the number of tasks in case study. And for evaluation the performance of proposed genetic algorithm, we compare to existing algorithm of one-sided and mixed model assembly line. The results show that the algorithm is outstanding in the problems with a larger number of stations or larger number of tasks.