• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.226-233
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• 2023

To create an environmentally sustainable fuel with a low sulfur concentration, requires alternative sulfur removal methods. During the course of this study, a high surface gamma alumina-supported ZnO nanocatalyst with a ZnO/-Al₂O₃ ratio of 12% was developed and tested for its ability to improve the activity of the oxidative desulfurization (ODS) process for the desulfurization of kerosene fuel. Scanning electron microscopy (SEM) and Brunauer-Emmett-Teller (BET) were used to characterize the produced nanocatalyst. In a digital batch baffled reactor (20~80 min), the effectiveness of the synthesized nanocatalyst was tested at different initial concentrations of dibenzothiophene (DBT) of 300~600 ppm, oxidation temperatures (25~70 ℃), and oxidation periods (0.5, 1, and 2 hours). The baffles included in the digital baffled batch reactor resist the swirling of the reaction mixture, thus facilitating mixing. The ODS procedure yielded the maximum DBT conversion (95.5%) at 70 ℃ with an 80-minute reaction time and an initial DBT level of 600 ppm. The most precise values of kinetic variables were subsequently determined using a mathematical modelling procedure for the ODS procedure. The average absolute error of the simulation findings was less than 5%, demonstrating a good degree of agreement with the experimental results acquired from all runs. The optimization of the operating conditions revealed that 99.1% of the DBT can be removed in 140 minutes.

• Journal of the Korean Ceramic Society
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• v.53 no.3
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• pp.317-324
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• 2016

Continued miniaturization and increasingly exact requirements for thin film deposition in the semiconductor industry is driving the search for new effective, efficient, selective precursors and processes. The requirements of defect-free, conformal films, and precise thickness control have focused attention on atomic layer deposition (ALD). ALD precursors so far have been developed through a trial-and-error experimental approach, leveraging the expertise and tribal knowledge of individual research groups. Precursors can show significant variation in performance, depending on specific choice of co-reactant, deposition stage, and processing conditions. The chemical design space for reactive thin film precursors is enormous and there is urgent need for the development of computational approaches to help identify new ligand-metal architectures and functional co-reactants that deliver the required surface activity for next-generation thin-film deposition processes. In this paper we discuss quantum mechanical simulation (e.g. density functional theory, DFT) applied to ALD precursor reactivity and state-of-the-art automated screening approaches to assist experimental efforts leading toward optimized precursors for next-generation ALD processes.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.6
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• pp.101-108
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• 2010

The drum clutch investigated in this study is formed in 5 forming steps, which are 1st deep drawing, 2nd deep drawing, restriking, embossing, and $Grob^{TM}$ processes. Dimensional accuracy of the final products greatly depends upon how much more accurate pre-form is manufactured in the previous forming processes before the $Grob^{TM}$ process. The deep drawing, restriking and embossing processes in which the pre-form is formed are very important and decisive steps. Thus in some cases, excessive strain by these operations causes dimensional inaccuracy and cracks initiated from the base and wall of the product. Process variables such as the punch shapes both of 1st and 2nd deep drawing, and punch angle were selected to evaluate the deformation characteristics. The optimum parameters were determined from forming simulations using commercial FEM codes, DEFORM and Tauchi method, specifically developed for metal forming simulation. Finally, experiments for the whole drum clutch forming processes were carried out to verify the optimized forming parameters and the analytical results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.129-132
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• 2003

Used cutting fluid from machining processes is harmful to both environment and human health. Chemical substances that provide the lubrication function in the machining process are toxtc to the environment if the cutting fluid is released to soil and water and caused serious health problems to workers who are exposed to the cutting fluid in both liquid and mist form. Recently. cost of using cutting fluid is increasing as the number and the extensiveness of environmental protection laws and regulations increase. Therefore, the use of cutting fluid in machining processes place an enormous burden on manufacturing companies to cover the additional costs associated with their use and protection of our environment. Current trends in manufacturing are focused on minimizing or eliminating the use of metalworking fluids in machining processes. And the increased costs for the disposal of waste products (swarf, coolants and lubricants), especially in industrially developed countries, has generated interest in dry machining. A variety of new techniques are testimony that new technology has rationalized further efforts to research and implement dry machining processes. This paper presents the developed equipment, the process optimization and the applications in the field of surface grinding for the new cryogenic dry machining using a compressed cooling air. The investigated new machining process method shows many advantages compared to conventional techniques with cutting fluid.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.802-810
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• 1998

The purpose of this study is to find the analytic solution of determining the optimal capacity of processes and storages to meet the product demand. Recent trend to reduce product delivery time and to provide high quality product to customer requires the increasing capacity of storage facilities. However, the cost of constructing and operating storage facilities is becoming substantial because of increasing land value, environmental and safety concern. Therefore, reasonable decision making about the capacity of processes and storages is important subject for industries. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ(Economic Order Quantity) model, trimmed with practical experience but the unrealistic assumption of EOQ model is not suitable for the chemical plant design with highly interlinked processes and storages. This study, a first systematic attempt for this subject, clearly overcomes the limitation of classical lot sizing method. The superstructure of the plant consists of the network of serially and/or parallelly interlinked processes and storages. A novel production and inventory analysis method, PSW(Periodic Square Wave) model, is applied. The objective function of optimization is minimizing the total cost composed of setup and inventory holding cost. The advantage of PSW model comes from the fact that the model provide a set of simple analytic solution in spite of realistic description of material flow between process and storage. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for the preliminary plant design confronting diverse economic situation.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.5
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• pp.831-837
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• 1997

Response surface methodology(RSM) was applied in roasting processes of Polygonatum odoratum roots in order to monitor Hunter color parameters and to optimize organoleptic properties of the tea. In roasting processing based on the central composite design with variations in roasting temperature (110~19$0^{\circ}C$) and roasting time(15~75min), coefficients of determinations($R^{2}$) of the models were above 0.9827(p<0.01) in Hunter color parameters and above 0.7748 in organoleptic properties. Hunter color L and $\Delta$E values of the powdered samples decreased with the roasting processes, whereas Hunter color a and b values increased up to around 59 min at 136$^{\circ}C$ and thereafter showed a decreased tendency. Organoleptic qualities on color, taste and aroma of Polygonatum odoratum tea were improved along with roasting processes, thereby estimating the optimum roasting conditions by RSM for the maximized qualities of organoleptic properties as a range from 127$^{\circ}C$ to 135$^{\circ}C$ and from 60min to 66 min. Hunter color a value(redness) was found to generate a similar response surface to that of organoleptic properties, showing the possibility of quality index in roasting processes of Polygonatum odoratum roots.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1163-1168
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• 2006

Manufacturing technology for the production of high value-added fine chemical products is emphasized and getting more attention as the diversified interests of customers and the demand of high quality products are getting bigger and bigger everyday. Thus, the development of advanced batch processes, which is the preferred and most appropriate way of producing these types of products, and the related technologies are becoming more important. Therefore, high-precision batch distillation is one of the important elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. Accordingly, proposing a process structure explanation and operation strategy of such processes including batch processes and batch distillation would be of great value. We investigate optimal operation strategy and production planning of multi-purpose plants consisting of batch processes and batch distillation for the manufacturing of fine chemical products. For the short-term scheduling of a sequential multi-purpose batch plant consisting of batch distillation under MPC and UIS policy, we proposed a MILP model based on a priori time slot allocation. Also, we consider that the waste product of being produced on batch distillation is recycled to the batch distillation unit for the saving of raw materials. The developed methodology will be especially useful for the design and optimal operations of multi-purpose and multiproduct plants that is suitable for fine chemical production.

• Transactions of the Korean hydrogen and new energy society
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• v.32 no.1
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• pp.11-40
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• 2021

Solid oxide fuel cell (SOFC) has received significant attention recently because of its potential for the clean and efficient power generation. The current manufacturing processes for the SOFC components are somehow complex and expensive, therefore, new and innovative techniques are necessary to provide a great deal of cell performance and fabricability. Three-dimensional (3D) printing processes have the potential to provide a solution to all these problems. This study reviews the literature for manufacturing the SOFC components using 3D printing processes. The technical aspects for fabrication of SOFC components, 3D printing processes optimization and material characterizations are discussed. Comparison of the SOFC components fabricated by 3D printing to those manufactured by conventional ceramic processes is highlighted. Further advancements in the 3D printing of the SOFC components can be a step closer to the cost reduction and commercialization of this technology.

• Journal of Distribution Science
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• v.13 no.11
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• pp.123-130
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• 2015

Purpose - Due to highly elevated levels of competition, many companies today have to face the problem of decreasing profits even when their actual sales volume is increasing. This is a common phenomenon that is seen occurring among companies that focus heavily on quantitative growth rather than qualitative growth. These two aspects of growth should be well balanced for a company to create a sustainable business model. For supply chain management (SCM) planners, the optimized, quantified flow of resources used to be of major interest for decades. However, this trend is rapidly changing so that managers can put the appropriate balance between sales volume and sales quality, which can be evaluated from the profit margin. Profit optimization is a methodology for companies to use to achieve solutions focused more on profitability than sales volume. In this study, we attempt to provide executional insight for companies considering implementation of the profit optimization system to enhance their business profitability. Research design, data, and methodology - In this study, we present a comprehensive explanation of the subject of profit optimization, including the fundamental concepts, the most common profit optimization logic algorithm -linear programming -the business functional scope of the profit optimization system, major key success factors for implementing the profit optimization system at a business organization, and weekly level detailed business processes to actively manage effective system performance in achieving the goals of the system. Additionally, for the purpose of providing more realistic and practical information, we carefully investigate a profit optimization system implementation case study project fulfilled for company S. The project duration was about eight months, with four full-time system development consultants deployed for the period. To guarantee the project's success, the organization adopted a proven system implementation methodology, supply chain management (SCM) six-sigma. SCM six-sigma was originally developed by a group of talented consultants within Samsung SDS through focused efforts and investment in synthesizing SCM and six-sigma to improve and innovate their SCM operations across the entire Samsung Organization. Results - Profit optimization can enable a company to create sales and production plans focused on more profitable products and customers, resulting in sustainable growth. In this study, we explain the concept of profit optimization and prerequisites for successful implementation of the system. Furthermore, the efficient way of system security administration, one of the hottest topics today, is also addressed. Conclusion - This case study can benefit numerous companies that are eagerly searching for ways to break-through current profitability levels. We cannot guarantee that the decision to deploy the profit optimization system will bring success, but we can guarantee that with the help of our study, companies trying to implement profit optimization systems can minimize various possible risks across various system implementation phases. The actual system implementation case of the profit optimization project at company S introduced here can provide valuable lessons for both business organizations and research communities.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.1-8
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• 2019

In this study, the multi-objective optimization method is attemped to optimize the hydrological model to estimate the runoff through two hydrological processes. HL-RDHM, a distributed hydrological model that can simultaneously estimate the amount of snowfall and runoff, was used as the distributed hydrological model. The Durango River basin in Colorado, USA, was selected as the watershed. MOSCEM was used as a multi-objective optimization method and parameter calibration and hydrologic model optimization were tried by selecting 5 parameters related to snow melting and 13 parameters related to runoff. Data from 2004 to 2005 were used to optimize the model and verified using data from 2001 to 2004. By optimizing both the amount of snow and the amount of runoff, the RMSE error can be reduced from 7% to 40% of the simulation value based on the initial solution at three SNOTEL points based on the RMSE. The USGS observation point of the outflow is improved about 40%.