• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.169-172
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• 2000

In this paper, an OMM (On-the-Machine Measuring) system has been developed, which can perform measuring and inspection of sculptured surfaces of die and mold, by use of a scanning-type touch probe mounted into the spindle of a NC machine. The calibration procedures of a scanning prove (SP2-1, Renishaw) and an algorithm for measuring surface points by a ball-nosed stylus have been studied. The system has been developed based on commercial CAM software (Z-Master 2000), and tested through measuring a plastic injection molding-die. Also some experimental results of the calibration and measuring for given surface positions are analyzed to verify its accuracy and reliability.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.585-588
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• 2003

As the advance in technology requires micro mechanical systems, the production methods for micro parts are of a great interest of many researchers. Although MEMS is one of the most popular methods. it can only produce 2D microstructures. The micro manufacturing with micro-mill and micro-lathe has a great potential for producing arbitrary 3D shapes and are being researched. In this paper, a PC based 5-axis milling machine with high precision was developed. To evaluate the machine performance, micro ribs and micro columns were machined. The machining experiments of micro impeller and micro turbine blade confirmed the possibility of micro system manufacturing by using the developed milling machine.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.1-7
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• 2020

As the demand for health screening increases, there is a need for efficient design of screening items. We build machine learning models for health screening and recommend screening items to provide personalized health care service. When offline, a synthetic data set is generated based on guidelines and clinical results from institutions, and a machine learning model for each screening item is generated. When online, the recommendation server provides a recommendation list of screening items in real time using the customer's health condition and machine learning models. As a result of the performance analysis, the accuracy of the learning model was close to 100%, and server response time was less than 1 second to serve 1,000 users simultaneously. This paper provides an adaptive and automatic recommendation in response to changes in the new screening environment.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.172-179
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• 1998

To quickly determine the effect of the substitute component on the machine's performance is very important in the design and manufacturing processes. And minimizing machine cost and maximizing machine quality mandate predictability of machine accuracy. In this study, in order to evaluate the effects of the component's geometric errors and dimensions on the machining accuracy of gantry-type 5-axis machining centers, a geometric error analysis and virtual manufacturing system are developed based on the mathematical model for the shape generation motion of machine tool considering the component's geometric errors and dimensions, the solid modeling techniques and so on.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.651-654
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• 1988

This paper proposes a microcode generating system which automatically generates the microcode of various target machine by inputing the intermediate language (MDIL) from the machine independent HLML-C (High Level Microprograming Language C) language. The MOP's (Microoperations) which is modeled 7-tuples generate to extend MDIL by table driven method with the information of translation table for each target machine. As compaction being considered and the hardware resource of target machine used, the conflicts of hardware elements are removed possibly. This proposed system is implemented with C language and yacc on VAX-11/750 (UNIX 4.3 BSD).

• 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 Industrial Technology
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• v.20 no.B
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• pp.189-194
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• 2000

In this paper, we present a BLDC Motor control for needle positioning and velocity control in the industrial sewing machine. In the industrial sewing machine, the fast acceleration control is needed, especially for a person who has a skill in operation of sewing machine for more products. And it is also needed to have a less noise and vibration. But the system which is made in a low price has no feedback system for a current control. Therefore we propose the method of velocity pattern that has an acceleration of velocity and Anti-windup algorithm. By the experiment, we confirmed that these manner have a good performance for low noise, low vibration and fast acceleration in the industrial sewing machine.

• Journal of Power Electronics
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• v.9 no.4
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• pp.575-581
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• 2009

In this paper two modes of operating a wound rotor induction machine as a generator at sub-and super-synchronous speeds in wind energy conversion systems are investigated. In the first mode, known as double fed induction generator (DFIG), the rotor circuit is fed from the ac mains via a controlled rectifier and a forced commutated inverter. Adjusting the applied rotor voltage magnitude and phase leads to machine operation as a generator at sub-synchronous speeds. In the second mode, the machine is operated in a slip recovery scheme where the slip energy is fed back to the ac mains via a rectifier and line commutated inverter. This mode is described as double output induction generator (DOIG) leading to increase the efficiency of the wind-to electrical energy conversion system. Simulated results of both modes are presented. Experimental verification of the simulated results are presented for the DOIG mode of operation, showing larger amount of power captured and better power factor when compared to conventional induction generators.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.90-97
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• 1996

The thermal deformation of a machine tool spindle influences the performance of the manufacturing systems for precision products. In this research, thermal analysis of a high speed machine tool spindle with the rolling bearing and the built-in motor is carried out by using Finite Difference Method. The thermal boundary conditions describing the heat generation in the bearing and built-in motor are considered in the simulation. And various convective boundary conditions are assumed with the empirical formula in the references. From the simulation results, the characteristics of each element affecting the dynamic thermal behaviour of the machine tool spindle system have been clarified. Therefore, this model can be well applied to the future development of the high speed spindle systems.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.1-11
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• 2017

In this paper, we design and implement PADIL(Prediction And Detection of Information Leakage) system that predicts and detect information leakage behavior of insider by analyzing network traffic and applying a variety of machine learning methods. we defined the five-level information leakage model(Reconnaissance, Scanning, Access and Escalation, Exfiltration, Obfuscation) by referring to the cyber kill-chain model. In order to perform the machine learning for detecting information leakage, PADIL system extracts various features by analyzing the network traffic and extracts the behavioral features by comparing it with the personal profile information and extracts information leakage level features. We tested various machine learning methods and as a result, the DecisionTree algorithm showed excellent performance in information leakage detection and we showed that performance can be further improved by fine feature selection.