• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.310-315
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• 2011

General portal machine represents a distinct weak spot concerning their structural behavior because of long protruding structure components, such as saddles and rams. The weak point causes the deformation of the machine tool and consequently rises a severe machining error. The purpose of this study is to improve the structural design of crossrail in order to minimize it's distortion. Tool Center Point (TCP) was chosen as a reference point for evaluating the distortion effect of a crossrail and topological optimization was adopted as a method of structural design improvement. The displacements of TCP according to the machining positions were investigated by structural analyses for both of original crossrail design and the improved one. The comparing results showed that the displacement of TCP could be reduced about 55% maximum.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.277-285
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• 1997

In this paper, the definition to flexibility is examined through the literature and re-classified to set up an evaluation model. Flexibility is classified into three categories to find the flexibility types for evaluation. The flexibility type called as manufacturing flexibility is defined and a model is developed to make the performance evaluation possible, The manufacturing flexibility has a heavy relationship to the machine flexibility; and 5 flexibility types out of 8 have relationship to the machine flexibility. This indicates that it is possible to have a pretty good evaluation measure if the machine flexibility related types could be evaluated using a model. There are four different inter-arrival times in the model. A big time saving is observed if the processing time is set equal to 72 second. This indicates that a flexibility affects the system a lot if the inter-arrival time is close to the processing time. The model used in this paper includes multi-processes in a production line with machine failure. However, development of realistic models with buffer between processes and some of the flexibility types not included in this model are remained for further research.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.131-135
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• 2021

Numbers of studies related to optimization of design of organic light emitting diodes(OLED) through machine learning are increasing. We propose the generative method of the image to assess the performance of the device combining with machine learning technique. Principle parameter regarding dark spot growth mechanism of the OLED can be the key factor to determine the long-time performance. Captured images from actual device and randomly generated images at specific time and initial pinhole state are fed into the deep neural network system. The simulation reinforced by the machine learning technique can predict the device parameters accurately and faster. Similarly, the inverse design using multiple layer perceptron(MLP) system can infer the initial degradation factors at manufacturing with given device parameter to feedback the design of manufacturing process.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.121-125
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• 2020

With miniaturization of semiconductor, the manufacturing process become more complex, and undetected small changes in the state of the equipment have unexpectedly changed the process results. Fault detection classification (FDC) system that conducts more active data analysis is feasible to achieve more precise manufacturing process control with advanced machine learning method. However, applying machine learning, especially in supervised learning criteria, requires an arduous data labeling process for the construction of machine learning data. In this paper, we propose a semi-supervised learning to minimize the data labeling work for the data preprocessing. We employed equipment status variable identification (SVID) data and optical emission spectroscopy data (OES) in silicon etch with SF6/O2/Ar gas mixture, and the result shows as high as 95.2% of labeling accuracy with the suggested semi-supervised learning algorithm.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.1-8
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• 2021

This study proposes a systems engineering approach for the development of an advanced planning & scheduling (APS) system for a cosmetic case manufacturing factory. The APS system makes production plans and schedules based on the injection process, which consists of 27 plastic injection machines in parallel to control recommended inventory of products. The system uses machine operation/failure information and defective product/work-in-process tracking information to support intelligent scheduling. Furthermore, a genetic algorithm model is applied to handle the complexity of heuristic rules and machine/quality constraints in this process. As a result of the development, the recommended inventory compliance rate is improved by scheduling the 30-day production plan for 15 main products.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.09a
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• pp.121-125
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• 2005

In this paper, the web-based monitoring system is developed for the process monitoring of mold manufacturing. The cutting force is measured by hall-sensors which is low cost and useful to be installed in machine tool indirectly. Specially, the current of main spindle in machine tool is converted into cutting force by various experiments. For effective emote monitoring, the interface that is able to offer the information of current process and cutting signal to client is establish.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.2
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• pp.76-90
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• 1986

This paper discusses the analysis of flexible manufacturing systmes design using computer simulation method. The simulation language employed is SIMAN which is a powerful tool to model flexible manufacturing systems. The important characteristics of FMS, its design and operational problems, and structures based on the number of NC machine tools and their layout are discussed for the appli- cations of FMS to manufacturing. A new algorithm for forming part families and machine groups has been proposed and its software is also developed. Simulation procedure using SIMAN for analysis of FMS designs is discussed and two design problems are analyzed and evaluated to illustrate systemstic procedure for analysis of FMS.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.760-761
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• 2019

Smart manufacturing is a process of integrating computer-related technologies in production and by doing so, achieving more efficient production management. The recent development of supercomputers has led to the broad utilization of artificial intelligence (AI) and machine learning techniques useful in predicting specific patterns. Despite the usefulness of AI and machine learning techniques in smart manufacturing processes, there are many fundamental issues with the direct deployment of these technologies related to data management. In this paper, we focus on solving the outlier detection issue in smart manufacturing applications. More specifically, we apply a state-of-the-art outlier detection technique, called Elliptic Envelope, to detect anomalies in simulation-based collected data.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.11-21
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• 1992

Modern manufacturing process requires machine intelligence to meet the demands for high technology products as well as intelligence-based operating skills to lessen human worker's intervene. To meet this trend there has been wide spread interest in applying artificial neural network(ANN) to the areas of manufacturing process monitoring and control. This paper addresses application problems in such processes as welding, assembly, hydroforming process and inspection of solder joints.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.1
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• pp.126-134
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• 1998

In order to increase the modeling power and productivity of CAD/CAM systems, demands for customization of CAD/CAM system increased. Customization of a CAM system involves making it easier to learn and use, adding new modeling features not supported in a general purpose CAM system, and providing parametric inputting mechanism. A customization from a commercial CAM system (OMEGA) has implemented for two dimensional free curve CNC glass scribing machine of medium size company in Cheonan. A CAD technician who has no CAM experience can operate this customized CAM system satisfactorily.