• Proceedings of the Membrane Society of Korea Conference
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• 1996.06a
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• pp.177-189
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• 1996

Raverase osmosis or ultrafiltration systems have generally been regarded as hard to validate about WFI production. Though the Japanese and US Pharmacopoeias have allowed distillation and RO to be applied to WFI production process, only water stills, especially multiple effects have practically been employed for parenteral water production. On the other hand, the latest analysis has shown that even distillate contains such volatile organic matters as trihalomethanes and traces of heavy metals at a little higher concentration than supposed. The JP requires TOC to be monitored in WFI process based on RO or UF systems to control the concentration below 300ppb, but very few monographs or papers have so far been published about the concentrations of organic volatile matters in distillate. (See table 1-1) Therefore, this paper proposes a new applicable WFI systems based on the result of purified water analysis with some membranes used in the process. A well combined membrane system with other units could be expected to provide less amount of impurities in membrane-treated water than in distillate.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• Journal of the Korean Society of Industry Convergence
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• v.12 no.2
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• pp.69-78
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• 2009

Dust in the fabric production sites is increased by the static electricity in air which is generated in the manufacturing process. The static electricity is shown in inverse proportion to humidity of the production sites. The optimum humidity rate for the filament in the production process has been established as 65~75%. Where as, average humidity rate of production site is estimated as 40%. Therefore, it is necessary to raise the humidity rate by 30% to maintain appropriate humidity to control generation of static electricity and dust in the production sites. In this study, a new air-jet water sprayer was developed and it can produce $10{\mu}m$ sprayed particles. When the air-jet water sprayer was operated on the production site dust generation rate was shown far below the environmental standard. It is assumed that when the air jet sprayers was applied to 1,000 fabric machines of 5 gloves making plants, its productivity and rates of operation will be improved by value of about 2.5 billion Won a year.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.487-494
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• 2013

Purpose: In this study, we propose the precision guided munitions verification methodology using the statistical analysis method has been proposed. and it can be applied to the precision guided munitions quality assurance work. Methods: This modeling is based on Failure Mode and Effects Analysis, Statistical Process Control, Defense Quality Managerment System, Production Readiness Review, Manufacturing Readiness Assesment and so on. Results: The Process Control Modeling that has the following procedures ; searching the critical to quality, statistical analysis by process, verify process. Moreover, the effectiveness of the methodology is verified by applying to the precision guided munitions. Conclusion: To achieve a analysis methods of statistical process control and verify process for precision guided munitions.

• Current Photovoltaic Research
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• v.4 no.3
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• pp.124-129
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• 2016

Recently industry has voiced a need for optimally designing the production process of low-cost, high-quality ingots by improving productivity and reducing production costs with the Czochralski process. Crystalline defect control is important for the production of high-quality ingots. Also oxygen is one of the most important impurities that influence crystalline defects in single crystals. Oxygen is dissolved into the silicon melt from the silica crucible and incorporated into the crystalline a far larger amount than other additives or impurities. Then it is eluted during the cooling process, there by causing various defect. Excessive quantities of oxygen degrade the quality of silicone. However an appropriate amount of oxygen can be beneficial. because it eliminates metallic impurities within the silicone. Therefore, when growing crystals, an attempt should be made not to eliminate oxygen, but to uniformly maintain its concentration. Thus, the control of oxygen concentration is essential for crystalline growth. At present, the control of oxygen concentration is actively being studied based on the interdependence of various factors such as crystal rotation, crucible rotation, argon flow, pressure, magnet position and magnetic strength. However for methods using a magnetic field, the initial investment and operating costs of the equipment affect the wafer pricing. Hence in this study simulations were performed with the purpose of producing low-cost, high-quality ingots through the development of a process to optimize oxygen concentration without the use of magnets and through the following. a process appropriate to the defect-free range was determined by regulating the pulling rate of the crystals.

• Management & Information Systems Review
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• v.22
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• pp.211-229
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• 2007

The ISO/TS16949 APQP goal of defect prevention and decrease of spread waste, is the customer satisfaction which leads a continuous improvement and profit creation. The quality expense where the most is caused by but with increase of production initial quality problem occurrence is increasing to is actuality. Like this confirmation amendment. with the problem which is forecast in the place development at the initial stage which it does completeness it does not confront not to be able, production phase to be imminent, the problem accumulates and it talks the development shedding of which occurs. In opposition, prediction confrontation. is forecast in development early stage to and it is a structure which does not occur a problem to production early stage. Like this development is a possibility of accomplishing competitive company from production phase. Which attains an goal of, chance cause it leads a APQP activity (common cause) with special cause prevention & detection the connection characteristic of the focus technique against a interaction is important. And the customer requirement satisfaction and must convert a APQP goal of attainment at the key characteristics action step. (1) The Prevention - with Design FMEA application prevention of the present design management/detection, (2) the Detection (prevention/detection) - with Process FMEA application prevention of the present process control/detection, (3) Special Cause - statistical process control (SPC) 4M cause spread removal, (4) Common Cause - statistical process control (SPC) the nothing zero defect which leads the continuous improvement back of spread with application it will be able to attain with application.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.4
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• pp.93-113
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• 1997

In studying an EOQ-like inventory model for a manufacturing process, a number of findings were made. The system can "go out of control" resulting in a relatively minor problem state or "break-down". When the production system is in the minor problem statei produces a number of defective items. It is assumed that each defective piece requires rework cost and related operations. Once the machine breakdown takes place, the production system produces severely defective items that are completely unusable. Each completely unusuable item is immediately discarded and incurs handling cost, scrapped raw material cost and related operations. Two investment options in improving the production process are introduced : (1) reducing the probability of machine breakdown, breakdowns, and (2) simultaneously reducing the probability of machine breakdowns and setup costs. By assuming specific forms of investment cost function, the optimal investment policies are obtained explicitly. Finally, to better understand the model in this paper, the sensitivity of these solutions to changes in parameter values and numerical examples are provided.amples are provided.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.53-62
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• 2016

The current trends of product customization and repair of high value parts with individual defects demand automation and a high degree of flexibility of the involved manufacturing process chains. To determine the corresponding requirements this paper gives an overview of manufacturing process chains by distinguishing between horizontal and vertical process chains. The established way of modeling and programming processes with CAx systems and existing approaches is shown. Furthermore, the different types of possible adaptions of a manufacturing process chain are shown and considered as a cascaded control loop. Following this it is discussed which key requirements of repair process chains are unresolved by existing approaches. To overcome the deficits this paper introduces repair features which comprise the idea of geometric features and defines analytical auxiliary geometries based on the measurement input data. This meets challenges normally caused by working directly on reconstructed geometries in the form of triangulated surfaces which are prone to artifacts. Embedded into function blocks, this allows the use of traditional approaches for manufacturing process chains to be applied to adaptive repair process chains.

• Journal of the Korean Chemical Society
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• v.54 no.2
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• pp.181-182
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• 2010

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.6
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• pp.139-146
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• 2019

The modular building system is a type of prefabricated construction method, and is an industrialized building system that transports, assembles, and completes a three-dimensional module manufactured in a factory to the site. The economics of a modular building system where 50 to 80% of the entire process takes place in a modular factory is dominated by productivity of the factory manufacturing process. Since the building of the module is finished by the combination of unit parts produced by each material, it is necessary to manage the process in each module unit. However, currently marketed process control programs do not reflect the features of these modular methods. In this paper, we introduce Modular Factory Design software(MFD 2019) that can make modular unit production plan which reflects production base(modular factory) and production target(application and number of modular units). In order to verify software compatibility and reliability, two production plans with different production methods were formulated and simulated.