• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.72-77
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• 2023

In many manufacturing settings, including the semiconductor industry, products are completed by producing and assembling various components. Sorting out from randomly mixed parts and classification operations takes a lot of time and labor. Recently, many efforts have been made to select and assemble correct parts from mixed parts using robots. Automating the sorting and classification of randomly mixed components is difficult since various objects and the positions and attitudes of robots and cameras in 3D space need to be known. Previously, only objects in specific positions were grasped by robots or people sorting items directly. To enable robots to pick up random objects in 3D space, bin picking technology is required. To realize bin picking technology, it is essential to understand the coordinate system information between the robot, the grasping target object, and the camera. Calibration work to understand the coordinate system information between them is necessary to grasp the object recognized by the camera. It is difficult to restore the depth value of 2D images when 3D restoration is performed, which is necessary for bin picking technology. In this paper, we propose to use depth information of RGB-D camera for Z value in rotation and movement conversion used in calibration. Proceed with camera calibration for accurate coordinate system conversion of objects in 2D images, and proceed with calibration of robot and camera. We proved the effectiveness of the proposed method through accuracy evaluations for camera calibration and calibration between robots and cameras.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.159-164
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• 2003

Location of stock in a warehouse directly affects the total materials handling expense of all goods moving through the warehouse. The purpose of this paper is to develop a storage policy in order picking warehouse, the block-based storage policy to minimize the total order picking time. In block-based storage policy, the rack is divided into blocks and items are assigned to each block based on the turn-over rate of each item and the average distance between the blocks and the dock. To demonstrate the performance of the proposed policy, we compare with the existing method called class-based storage policy under various matching methods.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.499-502
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• 2009

유비쿼터스 시대에서 요구하는 가장 핵심적인 요소기술 즉 인프라이다. 최근의 유통산업에서 크게 부각되고 있는 것은 지능형 매장운영과 Future Store(미래형 매장)이다. 이러한 매장의 지능화는 RFID 및 USN 등의 기술을 활용하여 적용되어 지고 있으며 또는 이로 인한 업무 프로세스의 개선을 통한 효율적인 매장운영과 고객의 쇼핑의 편리성을 제공하기 위한 서비스 개발에 초점이 맞춰져 있다. 본 논문에서는 효율적인 고객서비스를 위한 기본적인 인프라를 구축하고 고객의 참여를 통한 매장 운영의 간소화를 통하여 운영인력의 절감과 Picking 및 배달의 활성화를 통한 매장을 직접 방문하는 고객수의 감소로 인한 운영비용 감소효과와 지능형 시스템으로 인한 잉여 인력 및 비용을 고객서비스에 집중 가능하도록 하였다.

• IE interfaces
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• v.16 no.spc
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• pp.105-110
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• 2003

This paper deals with a performance evaluation model of transporters in refrigerate warehouse. This study focussed on determining refrigerate warehouse design to minimize the expected travel time to improve the transporter performance and to minimize the operating costs. This study proposes the important detail aspects of refrigerate warehouse design, operational parameters and congestions. For solving this problem, we have shown a mathematical model to compute the initial value of the system performance and also a simulation model using AutoMod. A systematic approach proposed in this study for an optimal planning of order-picking warehouse is known as an effective method for the planning of order-picking warehouse and a performance evaluation problem of refrigerate warehouse operation.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.248-254
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• 1993

This paper proposes the labeling method for solving bin-picking problem in robot vision. It has the processing steps such as image thresholding, region labeling, and moment computation. To determine a target object from object, the modified labeling method is used to. The moment concept applied to determine the position and orientation of target object. Finally, some experiment result are illustrated and compared with the results of conventional shrinking algorithm and collision fronts algorithm. The proposed labeling method has reduced processing time.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.177-188
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• 2022

Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO₂ storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2003.07a
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• pp.427-433
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• 2003

숙주세포가 분열될 때, 재조합 DNA 분자의 복제물이 자손에게 전달되며 거기서 벡터 복제가 일어난다. 수많은 세포 분열이 일어난 후, 동일한 숙주세포의 콜로니(colony), 혹은 클론(clone)이 생성된다. 이때 숙주세포의 분열은 배양액을 담은 용기에서 이루어진다. 박테리아 속의 배양된 콜로니에 재조합 DNA가 포함되어 있지 않으면 푸른색을 띠고, 재조합 DNA가 포함되어 있으면 흰색을 띠게된다. 이 흰색의 콜로니만을 추출해 내는 것이 바로 콜로니 픽킹(picking)이라 한다. (중략)

• Fibers and Polymers
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• v.1 no.1
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• pp.55-58
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• 2000

We present a new approach to bale laydown grouping, which improves the laydown to laydown uniformities, compared to conventional approaches. In this approach, we use a frequency-relative picking method based on an HVI quality index for cotton bale selection and laydown formation. We demonstrate the effectiveness of this approach by computer simulation on real HVI data of 1500 cotton bales. Simulation results show that the proposed method significantly outperforms random picking.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.41-45
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• 1998

본 연구는 자동물류센터에서 수요자들에게 운송하기 위한 제공품의 Order-Picking을 위한 로봇장착 적하장비를 이용할 경우의 최적 운송예약계획 수립을 위한 시뮬레이션 모델의 연구이다. 로봇장착 적하장비Order-Picking을 할 경우의 물류흐름의 효율성을 분석하고 시스템의 성능산정을 위한 시뮬레이션 모델을 개발하고 이를 이용한 최적 운송예약시스템의 운영계획을 수립하였다. 운송예약으로부터 운송량, 운반-도착지점 및 요구시산 등의 정보를 On-Line System으로 예약 받고 운송회사의 운송능력 등을 고려하여 최적운송계획을 수립하였다. 이를 위한 전산 프로그램을 개발하고 Sample 예제의 결과를 보였다.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.1
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• pp.77-87
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• 1989

This paper deals with an automated storage carrousel which handles work-in-process(WIP) such as small parts for kitting. The system has been used predominately for order picking applications. Throughput performance of the system can be measured by the inverse of the expected order picking time. Analytic models are developed for approximating the expected times under the "nearest-item" sequencing rule. The performance of the models are tested through computer simulation. The gap between the two is shown to be reasonably small.