• KSBB Journal
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• v.26 no.4
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• pp.341-346
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• 2011

This work is focused on the possibility of marine biomass Codium fragile as renewable resources for production of levulinic acid. In an effort to optimize the reaction conditions of levulinic acid production from Codium fragile, response surface methodology was applied. A total of 18 individual experiments were designed to investigate the effect of reaction temperature, catalyst amount, and reaction time. As a result, 4.26 g/L levulinic acid from Codium fragile was produced in the condition of $160.7^{\circ}C$ of reaction temperature, 3.9% of sulfuric acid, and 39.1 min of reaction time. This result will provide the useful information for chemical production from marine resource.

• IE interfaces
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• v.9 no.2
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• pp.159-171
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• 1996

In recent, most'of automobile industries adopt the concept of JIT production. According to the concept, the paternal manufacturers require their suppliers to supply parts just in time, so it is very important for a subcontractor to produce the parts in the appointed time of delivery. This study develops a production information system for Woosin Industry, which is one of such subcontractors of Hyundai Motors Company(HMC). The system is developed for use in Client/Server environment. In this study, the following three modules are developed, i. e., the production scheduling module, the sales management module to deal with the information about orders of HMC, delivery of parts, and bill collecting, and the module for supporting material requirements planning and purchase of material.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.461-468
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• 2004

The amount of $CO_2$ and $CH_4$ that were produced during biodegradation with were measured as function of time. Also, the settlements of landfill lysimeters were measured at the same time, and the relation with LFF(landfill gas) production was investigated. The effects of leachate recycle on the acceleration of settlement were studied by comparing two lysimeters. The gas production rate constant, $^{\kappa}_{LFG}$ is obtained to predict future gas production and settlement. These will be key role factors to predict gas production patterns and residual long-term settlement.

• Transactions of the Korean hydrogen and new energy society
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• v.24 no.4
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• pp.275-281
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• 2013

This study was conducted to increase the amount of bio-hydrogen production from microalgae(Chlorella vulgaris) in batch reactors by thermal pre-treatment. The optimization of thermal pre-treatment was conducted using statistic experimental design of response surface methodology. Two experimental parameters of temperature and reaction time were considered. The optimization condition was founded at the coded variables of <0.52, -0.07> corresponding to the experimental of heating temperature of $95.6^{\circ}C$ and reaction time of 57.9 min, respectively. Under the optimal condition, the maximum hydrogen production was predicted to 25.3mL $H_2/g$ dry cell weight (dcw), which was 9.1 times higher value of control(2.8mL $H_2/g$ dcw).

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.162-169
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• 1998

This study presents an single machine scheduling algorithm minimize lateness of product by controlling machining speed. Generally, production scheduling uses the information of process planning. But the production scheduling algorithm has not considered the control of machining speed in its procedures. Therefore, the purpose of this study is to consider the machining speed in production scheduling algorithm for efficient production scheduling. Machining time and machining cost required to manufacture a piece of a product are expressed as a unimodal convex function with respect to machining speed, so it has minimal point at minimum time speed or the minimum cost speed. Therefore, because of considering the machining cost, the control of machining speed for the algorithm is executed between minimum speed and maximum speed. An example is demonstrated to explain the algorithm.

• Journal of the military operations research society of Korea
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• v.26 no.2
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• pp.55-74
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• 2000

A knowledge-based with production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a method to reflect the dynamic nature of a system when we make inferences with a knowledge-based system. This paper suggests a strategy of dynamic inference that can be used to take into account the dynamic behavior of decision-making with the knowledge-based system consisted of fuzzy production rules. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by the AHP(Analytic Hierarchy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with the Min operator, into a single DM for the rule. In this way, the importance of attributes of a rule, which can be changed from time to time, can be reflected in an inference with fuzzy production systems.

• Microbiology and Biotechnology Letters
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• v.19 no.3
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• pp.281-289
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• 1991

Neurospora crassa (KCTC 6079) produces tyrosinase (EC 1.14.18.1) during sexual differentiation under derepressed conditions in the presence of inducers such as amino acid analogues, antimetabolites or protein synthesis inhibitors. The selection of inducer concentration and induction time as well as inducer type are critical for the optimization of the enzyme production. The best inducer was found to be cycloheximide. Since cycloheximide was toxic to the cells, an optimal inducer concentration and an optimal induction time were determined to maximize the enzyme production from batch cultures. Mathematical models for the cell growth and the enzyme production were proposed and used for process optimization. By optimizing the induction conditions, maximum tyrosinase productivity was increased significantly.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1070-1075
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• 2004

Many mid-sized companies in Korean automotive industry have attempted to solve the lack of human power, to control the quality of components, to improve the production rate, and to innovate the manufacturing line. The goals of this study are to analyze the production rate of an automotive component manufacturing line using simulation software, to construct a Flexible Automation Subassembly (FAS) system and to suggest an optimized layout design using FAS line. In this research, the simulation model for manufacturing line was developed and used the realistic data (production planning, component type, working order, process time, queue time, line rules, etc) of a medium sized company in Korean automotive industry. To complete this research, a simulation software 'ARENA' was used.

• JSTS:Journal of Semiconductor Technology and Science
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• v.10 no.1
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• pp.28-36
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• 2010

Hardware implementation methods for Artificial Neural Network (ANN) have been researched for a long time to achieve high performance. We have proposed a Network on Chip (NoC) for ANN, and this architecture can reduce communication load and increase performance when an implemented ANN is small. In this paper, a multiple NoC models are proposed for ANN, which can implement both a small size ANN and a large size one. The simulation result shows that the proposed multiple NoC models can reduce communication load, increase system performance of connection-per-second (CPS), and reduce system running time compared with the existing hardware ANN. Furthermore, this architecture is reconfigurable and reparable. It can be used to implement different applications of ANN.

• IE interfaces
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• v.11 no.2
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• pp.159-176
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• 1998

In the motor manufacturing system with the properties of short delivery and order based production, the process plan is performed individually for each order by the expert of process plan after the completion of the detail design process to satisfy the specification to be required by customer. Also it is hard to establish the standard process plan in reality because part routings and operation times are varied for each order. Hence, the production planner has the problem that is hard to establish the production schedule releasing the job to the factory because there occurs the big difference between the real time to be completed the process plan and the time to be required by the production planner. In this paper, we study the decision supporting system for the process plan based on knowledge base concept. First, we represent the knowledge of process planner as a database model through the modified POI-Feature graph. Then we design and implement the decision supporting system imbedded in the heuristic algorithm in the client/server environment using the ORACLE relational database management system.