• Journal of the Korean Society for Precision Engineering
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• v.22 no.7 s.172
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• pp.146-154
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• 2005

Recently, the high-speed and intelligence technology of machine tools are developed for the high efficiency of productivity Under the operating condition from the high-speed of machine tools, the various failure modes can occur in core units of manufacturing system. Therefore it is for the reliability concept of machine tool to be required in a design level. And the above-stated technology must be accommodated in the feeding and spindle subsystem, etc those are the core units of machine tools. In this study, we are developed the test-bed of sliding cover (C-plate) in order to evaluating reliability and estimating failure modes of feeding subsystem under operating conditions. The reliability experiment using the developed test-bed and the additional structural analysis executed on single and double structure. We found out the weak parts of sliding cover and were able to predict a life cycle from the experiment results. In this study, we propose the new C-plate model with double link structure to apply the high-speed machine tool in the fundamental guideline.

• Journal of the Korean Society of Industry Convergence
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• v.11 no.3
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• pp.121-125
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• 2008

Commutator which plays the major role in switching electric currents from AC to DC is composed of copper and molding compound. The longevity of the DC motors are mostly hampered by the improper machining of the parts. Smooth surface will be mandatory to create the proper air gap of the commutator. In this thesis the selection of the proper materials and tools, the design and analysis of machine structure and the final test procedures have been investigated to achieve the smooth cut surface of the commutators. The performance and the product of the newly manufactured machine has been compared with those of the existing one. And the test result shows the new sawing machine has better overall efficiency and durability.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.468-472
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• 2005

In this paper, the static and dynamic stiffness of the air bearing stage for micro-micro machine tool are examined experimentally. For stiffness and precision concerns, air bearing stages are adapted for 3-axis micro-milling machine which is size of $200x200\;mm^2$. The air bearings in the stage are preloaded by permanent magnets to achieve desired bearing clearance and stiffness for vertical direction. As the stiffness of the air bearing is primary interests, static stiffness test were performed on XY stage in Z direction and Z column in Y direction. Dynamic test were performed on XY stage and Z column, respectively. Both static and dynamic tests were performed in different air pressure conditions. The vertical stiffness of XY stage is about 9 N/ pm where Y stiffness of Z column is much smaller as $1\;N/{\mu}m$ because of the large moment generated by Y force on the column.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• Progress in Superconductivity and Cryogenics
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• v.23 no.4
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• pp.35-38
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• 2021

Conventional direct current (DC) rotating machines are usually used for crane and press machine using high torque in metal and steel industries, because of a constant output power along variable rotating speed. A general DC motor with permanent field magnets could not increase a magnetic flux density at a gap between armature coils and field magnets. However, a superconducting DC motor has field magnets composed with high temperature superconducting (HTS) coils and it could increase the magnetic flux density at the gap to over 10 times than those of a general DC motor by control the excitation current into HTS coils. The superconducting DC motor could be operated with extremely high torque and constant output power at a low rotational speed. In this paper, a 500 W superconducting DC rotating machine was conceptually designed with a LN₂ (Liquid Nitrogen) cooling method and the operation characteristics results of HTS field magnets were presented. The two no-insulation HTS magnets for a 500 W superconducting DC rotating machine were fabricated. The excitation current for the HTS magnets could be controlled from 0 to 40 A. This test results will be available to design large-sized HTS magnets for a number of hundred kW class superconducting DC rotating machine under LN₂ cooling system.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.150-154
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• 2024

In recent years, there are extensive researches on the applications of machine learning to the automation and decision support for medical experts during disease detection. However, the performance of machine learning still needs improvement so that machine learning model produces result that is more accurate and reliable for disease detection. Selecting the hyper-parameter that could produce the possible maximum classification accuracy on medical dataset is the most challenging task in developing decision support systems with machine learning algorithms for medical dataset classification. Moreover, selecting the features that best characterizes a disease is another challenge in developing machine-learning model with better classification accuracy. In this study, we have proposed an optimized decision tree model for heart disease classification by using heart disease dataset collected from kaggle data repository. The proposed model is evaluated and experimental test reveals that the performance of decision tree improves when an optimal number of features are used for training. Overall, the accuracy of the proposed decision tree model is 98.2% for heart disease classification.

• Journal of the Korean Society of Industry Convergence
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• v.5 no.3
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• pp.201-208
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• 2002

The machine tool which operates by hand is replacing by CNC machine tool to improve the quality of the product and the productivity in modem mechanic industry. The precision of machine part is influenced greatly the surface roughness by cutting condition of machine tool. So this study was performed to examine the aluminium surface roughness of section according to change of strength rating, nose radius, cutting speed, using live center. The results of this study are as follows; 1. In the case of 56mm diameter of test piece(length is below triple of diameter), whether establish the live center or not, doesn't influence to the surface roughness, and it is possible to make product without the live center. 2. The average surface roughness of 42mm diameter(length is quadruple of diameter) is similar to the 56mm diameter in the cutting condition of nose radius 0.8mm and cutting speed 140mm/min, but there are increases and differences in other cutting conditions. 3. In the case of test piece length more 70m/min(140m/mm) and nose radius improved greatly using the live center. 4. In the case of test piece length is quintuple of diameter, the nose radius must choose big tool and increase the cutting speed in preference live center establishment availability to improve that is surface roughness. Conclusively, if aluminum test piece length is fewer than triple of diameter, can process without establishing live center. If aluminum test piece length is more than quintuple of diameter, cutting conditions to improve surface roughness are (1) cutting speed (2) nose radius (3) whether the live center uses or not.

• Composites Research
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• v.33 no.5
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• pp.262-267
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• 2020

With increasing demands for high-speed machining and lightweight design of machine tools, increasing likeliness of generation of machine tool spindle vibrations has become an important issue. Spindle vibration has a significant impact on the surface finish of the workpiece in ultra-precision machining. It is necessary to resolve the machine tool spindle vibration in various machining processes to improve machining accuracy. In this paper, a TiC-SKH51 metal-matrix composite was used to suppress the vibration of the machine tool spindle. To confirm the dynamic characteristic of the TiC-SKH51 composite, impact hammer tests were conducted. After verifying the reliability of a finite element analysis (FEA) by comparing the results of the impact hammer test with the modal analysis using FEA, the analysis of the machine tool spindle model was performed. The FEA results show that the TiC-SKH51 composite applied machine tool spindle can be utilized to suppress the vibration generation.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.243-254
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• 2014

When building a testing environment with a testing platform, the configuration of test executor and its interface should be built to be appropriate for the system under test (SUT). That is, it is necessary to build the test executor and interface environment that can properly handle the input and output signals of SUT. If the testing platform is not extendable, it should be modified significantly whenever new SUTs and models are tested. It is a serious drawback that the test executor and interface configuration need to be modified depending on testing targets. To overcome the drawback, this paper proposes TEM(test Execution Machine), which allows for test executor to reconfigure its environment suitable to new SUTs by modifying the configuration file. The proposed TEM is verified through testing two real systems.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.91-99
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• 2009

Because of both precise measurement and efficient quality control, coordinate measuring machines(CMMs) have been widely used in the industry. The purpose of this paper is to present a method to estimate the CMM measurement uncertainty using design of experiments. A factorial design is applied to carry out the performance test proposed by ISO 10360 and to investigate CMM measurement errors associated to orientation and length of the length bar. In order to assess the measurement uncertainty for the performance test, an analysis of the uncertainty components that make up the uncertainty budget has been carried out. The procedure for evaluating the uncertainty of it follows GUM ("Guide to the expression of uncertainty in measurement"). The results show that the proposed method is suitable to investigate CMM performance and determine the contribution of machine variables to measurement uncertainty.