• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.204-208
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• 1998

The fundamental issues to evaluate machine tool's performance through simulation pertain to the physical models of the machine tool itself and of process while the practical problems are related to the development of the modular software structure. It allows the composition of arbitrary machine/process models along with the development of programs to evaluate each state of machining process. Surface roughness is one of the fundamental factors to evaluate machining process and performance of machine tool, but it is not easy to evaluate surface roughness due to its tribological complexity. This paper presents an algorithm to calculate surface roughness considering cutting geometry, cutting parameters, and contact dynamics of cutting between tool and workpiece as well as tool wear in turning process. The designed virtual machining system can be used to evaluate the surface integrity of a turned surface during the design and process planning phase for the design for manufacturability analysis of the concurrent engineering.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.19-33
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• 1999

The fundamental issues to evaluate machine tools performance through simulation pertain to the physical models of the machine tool itself and of process while the practical problems are related to the development of the modular software structure. It allows the composition of arbitrary machine/process models along with the development of programs to evaluate each state of machining process. Surface roughness is one of the fundamental factors to evaluate machining process and performance of machine tool, but it is not easy to evaluate surface roughness due to its tribological complexity. This paper presents an algorithm to calculate surface roughness considering cutting geometry, cutting parameters, and contact dynamics of cutting between tool and workpiece as well as tool wear in turning process. This proposed algorithm could be used in the designed virtual machining system. The system can be used to evaluate the surface integrity of a turned surface during the design and process planning phase for the design for manufacturability analysis of the concurrent engineering.

• Transactions of Materials Processing
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• v.28 no.2
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• pp.83-88
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• 2019

This paper introduces a new concept - on-line FE model, as applied to metal rolling. The new technology allows for completion of process simulation within a tiny fraction of a second without loss of high-level prediction accuracy inherent to FEM. The three steps of an on-line FE model design namely, process metamorphosis, mesh design, and process variable design, are described in detail. The procedure is demonstrated step by step through designing actual on-line models for the prediction of the dog-bone profile in edge rolling. The validity and prediction accuracy of the on-line FE models are analyzed and discussed.

• ETRI Journal
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• v.22 no.2
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• pp.1-10
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• 2000

Pattern recognition is one of the most common problems encountered in engineering and scientific disciplines, which involves developing prediction or classification models from historic data or training samples. This paper introduces a new approach, called the Representational Capability (RC) algorithm, to handle pattern recognition problems using radial basis function (RBF) models. The RC algorithm has been developed based on the mathematical properties of the interpolation and design matrices of RBF models. The model development process based on this algorithm not only yields the best model in the sense of balancing its parsimony and generalization ability, but also provides insights into the design process by employing a design parameter (${\delta}$). We discuss the RC algorithm and its use at length via an illustrative example. In addition, RBF classification models are developed for heart disease diagnosis.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.1-11
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• 1993

This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.6
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• pp.17-22
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• 2020

This study investigates the flow efficiency based on valve shape. Three models are designed for the throttle, ball, and butterfly valves. Results show that Flow Model B, representing the ball valve, demonstrates the fastest flow rate among the three models. Although pressure contours are present on the side surfaces of the valve wings for all models, Flow Model C, representing the butterfly valve, demonstrates to be under the least amount of applied pressure among the three models. The results of this study can be utilized to efficiently control the air flow through various types of valves.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.79-100
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• 1993

This paper proposes an idea of reverse modeling that analyzes LP models and then converts them into an object-oriented model repository. The process of reverse modeling consists of (1) identifying and analyzing source models by meta processor, (2) model decomposition and generalization to scan the models and divide them into model components, and (3) deriving model selection rules from the components by rule generator. Through the process, we can extract reusable model components and build a model base with model selectioon rules. Examples with models created by SML and MODLER modeling languages are given to illustrate the methods. The model base management capabilities provided by reverse modeling can increase the reusabioity of current modeling tools.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.8
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• pp.1-7
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• 2020

In this study, three models on the installation of automotive additional front bumper guard were designed and the structural analysis was carried out. The additional front bumper models B and C appears to be safer on stability instead of the basic front bumper model A. Model A with a simple structure is shown to have the safe region overall except in the area where the load is applied directly. Models B and C are shown to have the shortest lives at the regions where the bumpers are connected with each other. By comparing with the least fatigue lives at models A, B and C, Model B has the longest life with the best durability.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.16-21
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• 2020

The structural analyses were conducted with three models of pinion gears connected to the rack gear which is driven by the steering axle at an automobile. Three models 1, 2 and 3 are designed as the different pinion gears due to the vehicle type. The lower the value of maximum stress, the better the durability of model. Model 3 has the best durability among three models. Models 1 and 2 are expected to require the adjustment in order to improve the durability better. By the utilization of this study result, it is thought to apply at designing the pinion gear with durability at the automobile.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.859-864
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• 2012

Poisson regression and negative binomial regression are usually used to analyze counting data; however, these models are unsuitable for fit zero-inflated data that contain unexpected zero-valued observations. In this paper, we review the zero-inflated regression in which Bernoulli process and the counting process are hierarchically mixed. It is known that zero-inflated regression can efficiently model the over-dispersion problem. Vuong statistic is employed to compare performances of the zero-inflated models with other standard models.