• 산업경영시스템학회지
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• 제33권3호
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• pp.184-191
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• 2010

In the environment of 450mm wafers production known as the next-generation semiconductor production process, one of the most significant features is the full automation over the whole manufacturing processes involved. The full automation system for 450mm wafer production will minimize the human workers' involvement in the manufacturing process as much as possible. In addition, since the importance of an individual wafer processing increases noticeably, it is necessary to develop more robust scheduling systems in the whole manufacturing process than so ever. The scheduling systems for the next-generation semiconductor production processes also should be capable of monitoring individual wafers and collecting useful data on them in real time. Based on the information gathered from these processes, the system should finally have a real-time scheduling functions controlling whole the semiconductor manufacturing processes. In this study, preliminary investigations on the requirements and needed functions for constructing the real time scheduling system and transforming manufacturing environments for 300mm wafers to those of 400mm are conducted and through which the next generation semiconductor processes for efficient scheduling in a clustered production system architecture of the scheduler is proposed. Our scheduling architecture is composed of the modules for real-time scheduling, the clustered production type supporting, the optimal scheduling and so on. The specifications of modules to define the major required functions, capabilities, and the relationship between them are presented.

• Design & Manufacturing
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• 제15권1호
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• pp.48-56
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• 2021

The quality of products produced by injection molding process is greatly influenced by the process variables set on the injection molding machine during manufacturing. It is very difficult to predict the quality of injection molded product considering the stochastic nature of manufacturing process, because the process variables complexly affect the quality of the injection molded product. In the present study we predicted the quality of injection molded product using Artificial Neural Network (ANN) method specifically from Multiple Input Single Output (MISO) and Multiple Input Multiple Output (MIMO) perspectives. In order to train the ANN model a systematic plan was prepared based on a combination of orthogonal sampling and random sampling methods to represent various and robust patterns with small number of experiments. According to the plan the injection molding experiments were conducted to generate data that was separated into training, validation and test data groups to optimize the parameters of the ANN model and evaluate predicting performance of 4 structures (MISO1-2, MIMO1-2). Based on the predicting performance test, it was confirmed that as the number of output variables were decreased, the predicting performance was improved. The results indicated that it is effective to use single output model when we need to predict the quality of injection molded product with high accuracy.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.511-511
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• 1995

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2008년도 International Meeting on Information Display
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• pp.1005-1008
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• 2008

Electronic Paper Displays (EPDs) incorporating electrophoretic foils have made digital reading as pleasant as reading normal print. We will report on progress to replace glass-based displays with light and robust plastic EPDs using only a few extra process steps in a standard TFT-LCD factory.

• 세라미스트
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• 제21권2호
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• pp.83-88
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• 2018

There is close relation between the heat generation and the performance of electronic device. The durability and efficiency of the device are degraded due to heat generation. It is necessary to release the generated heat from an electronic device. Based on demands of the printed circuit board (PCB) manufacturing, the robust and reliable plating technique of PCB is necessary. In this study, we review various methods for improving the heat sink property. These methods were considered to enhance the adhesion between ceramic substrate as heat sink and metal layer as electrode.

• 대한기계학회논문집A
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• 제26권5호
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• pp.914-923
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• 2002

Recently, there has been considerable interest in micro gyroscopes made of silicon chips. It can be applied to many micro-electro-mechanical systems (MEMS): devices for stabilization, general rate control, directional pointing, autopilot systems, and missile control. This paper shows how the mechanical design of the gyroscope can be done using axiomatic design, followed by the application of the Taguchi robust design method to determine the dimensions of the parts so as to accommodate the dimensional variations introduced during manufacturing. Functional requirements are defined twofold. One is that the natural frequencies should have fixed values, and the other is that the system should be robust to large tolerances. According to the Independence Axiom, design parameters are classified into a few groups. Then, the detailed design process is performed fellowing the sequence indicated by the design matrix. The dimensions of the structure are determined to have constant values fur the difference of frequencies without consideration of the tolerances. It is noted that the Taguchi concept is utilized as a unit process of the entire axiomatic approach.

• 대한안전경영과학회지
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• 제14권1호
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• pp.155-165
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• 2012

This essay talks about research of robust design for quality improvement of production procedure of Wet Etchant. It suggested the optimum design method in consideration of specific capability value that is the way to maximize the quality of product in the production system by using Daguchi parameter design method while finding factors affecting product quality with analysis of production system of product A from producer D. Also, it set long term of 6months as noise factor and let it to be the robust design that can find the optimum condition of control factor that is dull to the changes of each month, that is the change in noise factor. The control factor which affects the product quality is decided as combination method, temperature of raw material, combination time and as there are too many possibilities for combination methods, we performed 4 methods first based on previous research data then derived three ways with product that passed SPEC and set as the factor. As a result of application of optimum production procedure suggested in this essay to the actual production process with its standardization, there was a effect of drop of more than 10particles in comparison to the particle number of previous product and also it brought the effect that resulted the stable number of particle of under 30 that is what the client company suggested.

• Computers and Concrete
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• 제23권6호
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• pp.433-444
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• 2019

As rice husk ash (RHA) is not produced in controlled manufacturing process like cement, its properties vary significantly even within the same lot. In fact, properties of Rice Husk Ash Based Concrete (RHABC) are largely dictated by uncertainty leading to huge deviations from their expected values. This paper proposes a Robust Cost Optimization (RCO) procedure for RHABC, which minimizes such unwanted deviation due to uncertainty and provides guarantee of achieving desired strength and workability with least possible cost. The RCO simultaneously minimizes cost of RHABC production and its deviation considering feasibility of attaining desired strength and workability in presence of uncertainty. RHA related properties have been modeled as uncertain-but-bounded type as associated probability density function is not available. Metamodeling technique is adopted in this work for generating explicit expressions of constraint functions required for formulation of RCO. In doing so, the Moving Least Squares Method is explored in place of conventional Least Square Method (LSM) to ensure accuracy of the RCO. The efficiency by the proposed MLSM based RCO is validated by experimental studies. The error by the LSM and accuracy by the MLSM predictions are clearly envisaged from the test results. The experimental results show good agreement with the proposed MLSM based RCO predicted mix properties. The present RCO procedure yields RHABC mixes which is almost insensitive to uncertainty (i.e., robust solution) with nominal deviation from experimental mean values. At the same time, desired reliability of satisfying the constraints is achieved with marginal increment in cost.

• Biotechnology and Bioprocess Engineering:BBE
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• 제5권2호
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• pp.118-122
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• 2000

A comlementary call line CR2 is curretly used to propagte the Disabled Infectious Single Cycle Herpes Simplex Virus Typee2 (DISC HSV-2) on a small Iaboratory scale upto 15 L. These cultures are initiated by passaging the cells from roller bottle cultures. Whilst this is suitable for the laboratory scale it is totally impractical for use in seeding an industrial manufacturing scaled version of the culture. It is paramount to have a robust system for passaging cells from a small microcarrierier culture system to a larger one by a serial subculturing regime. Here we report on the successes we have had in our laboratory in scaling up out production system for the DISC HSV-2 from small 1-L cultures to a 50-L vessel with the maintenance of the viral productivity. Ease of use, reproducibility and the need to minimise overall production time were factors which were taken into consideration whils developing our procedures. We were aware of the need to keep a production train simple and as short as possible as this was the amall scale study for an envisaged manufacturing process.

• 한국생산제조학회지
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• 제6권1호
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• pp.7-17
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• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.