• 경영과학
• /
• 제12권1호
• /
• pp.1-17
• /
• 1995

The success of cell manufacturing applications in FMS rests on the effective cell formation to maintain the independent relations both between machine cells and between part families. This paper presents an integrated method for concurrent formation of cells and families with no E.E (Exceptional Element) in FMS with alternative routings. To determine the maximum number of cell and family with no E.E, mathematical conditions and properties are derived. New concept of nonsimilarity is introduced for each machine and part based on machine-operation incidence matrix and part-operation incidence matrix. To concurrently form the cells and families, integer programming based mathematical models are developed. For the predetermined number of cell or family, model I is used to identify whether E.E exists or not. Model II forms cells and families considering only nonsimilarity. But model III can consider nonsimilarity and processing times. The proposed method is tested and proved by using numerical examples.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
• /
• pp.201-203
• /
• 2005

The best method to study language is to talking with a native speaker. A voice recognition technology can be used to develope a language study machine. SD(Speaker dependant) and SI(speaker independant) voice recognition method is used for the language study machine. MP3 Player. FM Radio. Alarm clock functions are added to enhance the value of the product. The machine is designed with a DSP(Digital Signal Processing) chip for voice recognition. MP3 encoder/decoder chip. FM tumer and SD flash memory card. This paper deals with the application of SD ad SD voice recognition. flash memory file system. PC download function using USB ports, English conversation text function by the use of SD flash memory. LCD display control. MP3 encoding and decoding, etc. The study contents are saved in SD flash memory. This machine can be helpful from child to adult by changing the SD flash memory.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
• /
• pp.309-314
• /
• 2001

The balance of high speed spindle system with high precision rotation like grinding machine is very important. Traditionally, we use trial and error method to balance the spindle. It takes much time. So we are developing the automatic balancing equipment being used in the grinding machine. The balancing head we develop is wireless. It will be used high-speed grinding machine. We use influence coefficient method to control the automatic balancer. Experiments are based on automatic and manual balancing. We perform test of the vibration filter. It helps to remove noise. The filter and experiments with automatic balancing controller show that automatic balancing control can be successfully achieved with the quick response and good stability characteristics.

• 한국공작기계학회논문집
• /
• 제13권1호
• /
• pp.1-8
• /
• 2004

Thermal distortion is a critical issue in machine tools, especially in high speed machining. This is the reason why recent machine tools have thermal compensation function. To compensate thermal distortion, it is necessary to make a model that has some relationship between temperature and deformation. Various experimental methods ye widely been used in thermal test: constant spindle speed, unit step speed increase, random spindle speed, etc. This paper focuses on which type of spindle operation condition is good for thermal experiment. Also, experimental data is modeled using multiple linear regression models and compared each other to select a method. Consequently, it turned out at e condition of 75％ constant of maximum spindle speed is good enough to generate temperature and distortion data.

• Journal of the Korean Statistical Society
• /
• 제36권1호
• /
• pp.175-182
• /
• 2007

The support vector machine has been successful in many applications because of its flexibility and high accuracy. However, when a training data set is large or imbalanced, the support vector machine may suffer from significant computational problem or loss of accuracy in predicting minority classes. We propose a modified version of the support vector machine using the K-means clustering that exploits the information in class labels during the clustering process. For large data sets, our method can save the computation time by reducing the number of data points without significant loss of accuracy. Moreover, our method can deal with imbalanced data sets effectively by alleviating the influence of dominant class.

• 한국정밀공학회지
• /
• 제13권1호
• /
• pp.98-107
• /
• 1996

The use of composite hyperpatch model is proposed to predict a machine tool positional error over the entire work space. This is an appropriate representation of the distorted work space. This model is valid for any configuration of 3-axis machine tool. Tool position, which is given NC data or CL data, contains error vector in actual work space. In this study, off-line compensation scheme was investigated for tool position error due to inaccuracy in machine tool structure. The error vector in actual work space is corrected by the error model using Newton-Raphson method. The proposed error compensation method shows the possibility of improving machine accuracy at a low cost.

• 한국생산제조학회지
• /
• 제19권3호
• /
• pp.307-312
• /
• 2010

In this study, advanced computational technique for mechatronic analysis has been developed for the efficient design and test of typical machine tool models. Flexible multi-body dynamic (FMBD) analysis method combined with motion controller including control logics is used to simulate typical operation conditions. The present FMBD machine tool model is composed of flexible column structure, rigid body spindle, vertical motion guide (arm) and screw elements. Driving motor clement with rotating degree-of-freedom is interconnected and governed by the designed Matlab Simulink control logic, and then the position of the spindle is feedback into the control logic. It is practically shown from the results that the investigation of designed machine tools with controller can be effectively conducted and verified.

• 산업공학
• /
• 제2권2호
• /
• pp.15-24
• /
• 1989

When we design, plan, and schedule for group technology, the limitation on the machine cells and cell size may occur. The purpose of this study is to find machine cells and part families to minimize the exceptional elements, constraining both the number of machine cells and the cell size. To solve this problem, the algorithm extending Kusiak's p-median method is proposed. In the proposed algorithm, the method finding initial solution and reducing the number of constraints is presented for computational efficiency. The proposed algorithm is evaluated and compared with well-known algorithms for machine-part group formation in terms of the exceptional elements. An example is shown to illustrate the proposed algorithm.

• Industrial Engineering and Management Systems
• /
• 제11권1호
• /
• pp.26-29
• /
• 2012

In order to deal with the classification problems of type-2 fuzzy training samples on generalized credibility space. Firstly the type-2 fuzzy training samples are reduced to ordinary fuzzy samples by the mean reduction method. Secondly the definition of strong fuzzy linear separable data for type-2 fuzzy samples on generalized credibility space is introduced. Further, by utilizing fuzzy chance-constrained programming and classic support vector machine, a support vector machine based on type-2 fuzzy training samples and established on generalized credibility space is given. An example shows the efficiency of the support vector machine.

• Earthquakes and Structures
• /
• 제16권6호
• /
• pp.679-690
• /
• 2019

This paper presents machine learning methods using Support Vector Machine (SVM) and Multilayer Perceptron (MLP) to analyze optimal damper distribution for structural vibration control. Regarding different building structures, a genetic algorithm based optimization method is used to determine optimal damper distributions that are further used as training samples. The structural features, the objective function, the number of dampers, etc. are used as input features, and the distribution of dampers is taken as an output result. In the case of a few number of damper distributions, multi-class prediction can be performed using SVM and MLP respectively. Moreover, MLP can be used for regression prediction in the case where the distribution scheme is uncountable. After suitable post-processing, good results can be obtained. Numerical results show that the proposed method can obtain the optimized damper distributions for different structures under different objective functions, which achieves better control effect than the traditional uniform distribution and greatly improves the optimization efficiency.