• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.17 no.6
• /
• pp.24-30
• /
• 2018

Dental implants are currently widely used as artificial teeth due to their good chewing performance and long life cycle. A dental implant consists of an abutment as the upper part and a fixture as the lower part. When chewing forces are repeatedly applied to a dental implant, gap at the interface surface between the abutment and the fixture is often occurred, and results in some deteriorations such as loosening of fastening screw, dental retraction and fixture fracture. To cope with such problems, a sealing-type abutment having a number of grooves along the conical-surface circumference was previously developed, and shows better sealing performance than the conventional one. This study carries out optimization of the groove shape by genetic algorithm(GA) as well as structural analysis in consideration of external chewing force and pretension between the abutment and the fixture. The overall optimization system consists of two subsystems; the one is the genetic algorithm with MATLAB, and the other is the structural analysis with ANSYS. Two subsystems transmit and receive the relevant data with each other throughout the optimization processes. The optimization result is then compared with that of the conventional one with respect to the contact pressure and the maximum stress. The result shows that the optimized model gives better sealing performance than the conventional sealing abutment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.79-82
• /
• 2019

This study aims to design and implement automated SEO tools that has applied the artificial intelligence techniques for search engine optimization (SEO; Search Engine Optimization). Traditional Search Engine Optimization (SEO) on-page optimization show limitations that rely only on knowledge of webpage administrators. Thereby, this paper proposes the metadata generation system. It introduces three approaches for recommending metadata; i) Downloading the metadata which is the top of webpage ii) Generating terms which is high relevance by using bi-directional Long Short Term Memory (LSTM) based on attention; iii) Learning through the Generative Adversarial Network (GAN) to enhance overall performance. It is expected to be useful as an optimizing tool that can be evaluated and improve the online marketing processes.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.1
• /
• pp.79-87
• /
• 2017

The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.3
• /
• pp.305-312
• /
• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.

• The Korean Journal of Food And Nutrition
• /
• v.21 no.4
• /
• pp.391-396
• /
• 2008

In this study, we attempted to optimize the fermentation processes in the production of lactic acid juice with 20% Maesil(Prunus mume) extract using Lactobacillus plantarum isolated from Kimchi, assessing a variety of pH, temperature, sugar compositions, and sugar concentrations. In the preparation of fermented Maesil(Prunus mume) extract, the optimal pH and fermentation temperature were 4.0 and $35^{\circ}C$, respectively. When the effects of various sugar sources and concentrations on lactic acid fermentation were assessed, 15% fructose was shown to yield more acid productivity than was observed with other sugar sources. The optimum composition, on the basis of our sensory evaluations, was determined to be a fructose concentration of 15% and a fermentation time of $72{\sim}96$ hours.

• Journal of the military operations research society of Korea
• /
• v.7 no.1
• /
• pp.118-138
• /
• 1981

In many response surface optimization problems for industrial processes, there are more than two responses of interest, and we want to find the optimal levels of the factors that influence the responses. This paper is to propose how to set up the desirability functions to find the optimum for a given set of data, and to propose how to analyse the data and the desirability functions to determine an optimal operating condition for the factors. To implement the proposed method in practice, a FORTRAN computer program was written and explained. Finally, an industrial example is illustrated to explain the proposed technique and the source list of the computer program is attached for the users.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 1998.11a
• /
• pp.556-567
• /
• 1998

Robust design in industry is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise ratio(SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure. in the two different experimental design(product array, combined array) approaches.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.10
• /
• pp.832-835
• /
• 2003

The objective of this study is to investigate the possibility of chemical process synthesis purely based on mathematical programming when given an objective, feed conditions, product specifications, and model equations for available process units. A method based on a state space approach is proposed, and applied to an example problem with a reactor, a heat exchanger, and a separator. The results indicate that a computer can automatically synthesize an optimal process without any heuristics or expertise in process design provided that global optimization techniques are improved to be suitable for large problems.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1870-1873
• /
• 2004

The objective of this study is to investigate the possibility of chemical process synthesis purely based on mathematical programming when given an objective, feed conditions, product specifications, and model equations for available process units. A method based on a state space approach is proposed, and applied to an example problem with a reactor, a heat exchanger, and a separator. The results indicate that a computer can automatically synthesize an optimal process without any heuristics or expertise in process design provided that global optimization techniques are improved to be suitable for large problems.

• Journal of the Korean Chemical Society
• /
• v.56 no.2
• /
• pp.257-263
• /
• 2012

The selection of suitable delignification conditions and optimization of process variables is crucial to the successful operation of chemical pulping processes. Soda pulping of Carpolobia lutea was investigated, as an alternative raw material for pulp and paper production. The process was optimized under the influence of three operational variables, namely, temperature, time and concentration of cooking liquor. Equations derived using a second - order polynomial design predicted the pulp yield and lignin dissolution with errors less than 8% and 11% respectively. The maximum variations in the pulp yield using a second order factorial design was caused by changes in both time and alkali concentration. Optimum pulp yield of 43.87% was obtained at low values of the process variables. The selectivity of lignin dissolution was independent of the working conditions, allowing quantitative estimations to be established between the pulp yield and residual lignin content within the range studied.