• Journal of the Korea Safety Management & Science
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• v.6 no.4
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• pp.155-170
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• 2004

Among the semiconductor If-chips, unlike memory chips, a majority of Application Specific IC(ASIC) products are produced by customer orders, and meeting the customer specified due date is a critical issue for the case. However, to the one who understands the nature of semiconductor manufacturing, it does not take much effort to realize the difficulty of meeting the given specific production due dates. Due to its multi-layered feature of products, to be completed, a semiconductor product(called device) enters into the fabrication manufacturing process(FAB) repeatedly as many times as the number of the product specified layers, and fabrication processes of individual layers are composed with similar but not identical unit processes. The unit process called photo-lithography is the only process where every layer must pass through. This re-entrant feature of FAB makes predicting and planning of due date of an ordered batch of devices difficult. Parallel machines problem in the photo process, which is bottleneck process, is solved with restricted roll out algorithm. Roll out algorithm is a method of solving the problem by embedding it within a dynamic programming framework. Restricted roll out algorithm Is roll out algorithm that restricted alternative states to decrease the solving time and improve the result. Results of simulation test in condition as same as real FAB facilities show the effectiveness of the developed algorithm.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.98-103
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• 2019

A more accurate method of feature point extraction and matching for three-dimensional reconstruction using low-resolution images of crops is proposed herein. This method is important in basic computer vision. In addition to three-dimensional reconstruction from exact matching, map-making and camera location information such as simultaneous localization and mapping can be calculated. The results of this study suggest applicable methods for low-resolution images that produce accurate results. This is expected to contribute to a system that measures crop growth condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1626-1629
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• 2003

The study is expressed on the web browser using virtual reality of developer manufacturing process and method or manufactured goods conviction for designer and developer with visualized model. This study purpose of basic feature with VRML file and Java and VRML with AWT to get WC code was presented. The study process is equal to the real thing modeling on using Pro/Engineer and exports on the VRML1.0. The condition converts VRML1.0 to VRML2.0 on the CROSS ROADS. And then Cosmo World is coding and manufacturing simulation is expressed on the Cosmo Player.

• Korean Journal of Organic Agriculture
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• v.21 no.3
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• pp.305-319
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• 2013

In this study, it is intended that utilize the LCA (Life Cycle Assessment) method, to evaluate the environmental impact of wood pellet manufacturing facility. As mentioned above, wood pellet manufacturing facility of 20 has produced wood pellets as a raw material sawdust and wood in our country. In this study, in order to feature manufacturing process of wood pellets that resemble almost necessary to analyze evenly size and characteristics of various equipment whether these reasonable, the characteristics of the equipment may be different, the production of 20 places I surveyed the facility one central timber distribution center one large scale most of the equipment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.229-244
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• 2004

This study addresses the problem of flexible technology acquisition in multi-product market when demands are uncertain. We confine the concept of flexibility to the ability of manufacturing system to produce a number of different types of products, called product-mix flexibility type. And an analytical model in which economies of scope is incorporated explicitly as a feature of flexible technology is presented to find the optimal investment decision to acquire flexible technology and optimal production planning. The characteristics of optimal investment strategy related to capacity and production planning are discussed.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.135-142
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• 2005

This study addresses the problem of flexible technology acquisition in a multi-product market when demands are uncertain. We confine the concept of flexibility to the ability of manufacturing system to produce a number of different types of products, called a product-mix flexibility type. And an analytical model in which the economies of scope are incorporated explicitly as a feature of flexible technology is presented to find the optimal investment decision to acquire flexible technology and optimal production planning. The characteristics of optimal investment strategy related to capacity and production planning are discussed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.197-202
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• 2005

An aspheric lens is one of a key point optical element in the optical industry. The feature of an aspheric lens is not to have the spherical aberration. An aspheric lens is also essential element for high-precision and light-weight in the optical machine. Generally it have been used in a tailor progression an aspheric lens modelling much. In this study we applied a lay back-tracer using a index of refraction to draw a creative aspheric lens. Also we developed the automatic design program for aspheric lens. We manufactured the aspheric lens and executed a comparison experiment for refraction situation of shape and straightness experiment to inspect the drawn aspheric lens in this study.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.369-377
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• 2023

In the industrial manufacturing sector, quality control is pivotal for minimizing defect rates; inadequate management can result in additional costs and production delays. This study underscores the significance of detecting texture defects in manufactured goods and proposes a more precise defect detection technique. While the DFR(Deep Feature Reconstruction) model adopted an approach based on feature map amalgamation and reconstruction, it had inherent limitations. Consequently, we incorporated a new loss function using statistical methodologies, integrated a skip connection structure, and conducted parameter tuning to overcome constraints. When this enhanced model was applied to the texture category of the MVTec-AD dataset, it recorded a 2.3% higher Defect Segmentation AUC compared to previous methods, and the overall defect detection performance was improved. These findings attest to the significant contribution of the proposed method in defect detection through the reconstruction of feature map combinations.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.4
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• pp.120-126
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• 1989

IC chip layout pattern recognition algorithms using image processing techniques are being developed for the automation of manufacturing and inspecting chips. Recognitioin of chip pattern requires feature extraction from nach rrame of chip image adn needs to match the feature data through all frames. In this paper, vertex position and form having layout information are extracted by the feature straightening algorithm, and global coordinates of layout pattern are extracted by the feature straightening algorithm, and global coordinates of layout pattern are obtainnd by vertex form matching from the overlapped area of neighbour frame.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.