• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.185-189
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• 2001

In order to prevent the production defects the optimum design of product, jig and fixture putting in the field is very significant manufacturing method. Drilling Jig is the device according to industrial demand for multi manufacturing products on the growing at alarming rate. In the field of design and making for machine tool working, welding, assembling with jig and fixture for mass production is a specific division. They require analysis of many kinds of important factors, theory and practice of machine tool operating process and jig & fixture structure, machining condition for tool making, tool materials, heat treatment of jig & fixture components, know-how and so on. In this study we designed and constructed a drilling jig of mass production and performed tryout under the Auto CAD, Auto Lisp database, that we made by database, and window environment. Especially this study is reveals with the analysis of part drawing, jig planning, jig design etc, and then the result of drill jig's making try out.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.3
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• pp.254-262
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• 2008

The objective of the proposed study is to produce a tool-condition monitoring (TCM) strategy that will lead to a more efficient and economical drilling tool usage. Drill-wear monitoring is an important attribute in the automatic cutting processes as it can help preventing damages of the tools and workpieces and optimizing the tool usage. This study presents the architectures of a multi-layer feed-forward neural network with back-propagation training algorithm for the monitoring of drill wear. The input features to the neural networks were extracted from the AE signals using the wavelet transform analysis. Training and testing were performed under a moderate range of cutting conditions in the dry drilling of steel plates. The results indicated that the extracted input features from AE signals to the supervised neural networks were effective for drill wear monitoring and the output of the neural networks could be utilized for the tool life management planning.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.148-152
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• 2000

Detection of tool wear is very important in automated manufacturing. This paper presents tool condition monitoring system based on the wavelet analysis of the AC servo motro current in drilling and milling process. The current measurement system is relatively simple and its mounting will not affect machining operations. The discrete wavelet transform was used to decompose the current signal of a spindle AC servo motor in time - frequency domain. The feature vectors were extracted from the decomposed signals and compared for normal and wear condition. The results show the possibility for the effective application of wavelet analysis to tool condition monitoring.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1995.03a
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• pp.9-16
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• 1995

The thermal deformation of 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 using Finite Difference Method. The thermal boundary conditions describing the hear 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 systems have been clarified. This model can be well applied to the future development of the high speed spindle systems.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.41-43
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• 2001

This paper presents a Web-based educational tool for Power System Engineering, especially for power engineers. This tool has Web-oriented educational courses for power system education. The Web-based learning has become more popular year by year in the various fields[1-2]. The proposed educational tool provides some courses such as power system introduction Course, KEPCO's system introduction Course, Power system devices Course, Power Flow Course, OPF Course, ELD Course, Stability Analysis Course, Fault analysis Course, Voltage & Frequency control Course, and power system planning & operation Course. Finally, it will be scheduled to install for the education tool of the power system engineering for KEPS[3].

• Journal of Korean Academy of Nursing
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• v.33 no.6
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• pp.772-783
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• 2003

Purpose: This study was performed to measure the nursing service perceived value by consumer and providers, and to investigate the relationship among nursing service, general satisfaction and hospital revisiting intent, and to examinate the tools that measures nursing service's reliability, construct validity and usefulness. Method: The questionnaire was developed and distributed to 300 patients and 210 nurses at three general hospitals. For data analysis, SPSS/PC program was used. Result: The nursing service perceived value by providers is higher than that by consumers. There are distinctive difference in the expectation, and importance and performance values of the nursing service perceived. In examination of the relationship among nursing service, general satisfaction and hospital revisiting intent, nursing service has a deep relationship with general satisfaction, but doesn't have relationship with hospital revisiting intent. The tool that measures nursing service has a good reliability and construct validity. In analysis on the usefulness between the tools, SERVPERF tool is more useful than SERVQUAL tool. conclusion: The nursing service perceived value by consumer is different that by providers, and the tool that measures nursing service has a good reliability and construct validity. The SERVPERF tool is more useful than SERVQUAL tool.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.993-996
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• 2005

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, which has many advantages such as good quality, low cost and rapid machining time. but it also has problems like tool break, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is effected by the milling conditions whose evaluated parameters are spindle, feedrate, and width of cut. The experiments are carried out by full factorial design of experiments using and orthogonal array. This paper shows optimal combination and mathematical model for tool life, and the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.59-69
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• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1630-1641
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• 2010

LCC can be defined as "the sum of present values of investment costs, capital costs, installation costs, energy costs, operating costs, maintenance costs, and disposal costs over the life-time of the project, product, or measure." LCCA involves estimating the costs and timing associated with each alternative over a selected analysis period and conversion of those costs to economically comparable values considering the time-value of money. The several Excel-Based LCC tools found on the internet are described in this paper. Also, This paper performed an analysis of the existing LCC commercial tools, assessing various aspects of each program. The goal was to evaluate the best features of each tool and to identify the requirements for LCC evaluation of Urban Transit Vehicle. The LCC tools are developed to address problems in many different areas and a tool developed and structured for one area cannot generally be used in another area. No general LCC tool exists and if one is needed for Urban Transit Vehicle it has to be developed by the project. Since a full LCC can be very complex it is likely that this Excel-Based LCC tool should be a small and simple tool for quick cost estimates. This paper presents a LCC tool consisting of eight excel sheets, which are "Project", "CBS", "PBS", "PM", "CM", "Others", "LCC Result" and "Diagram".

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.1
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• pp.83-86
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• 2005

This study is predicted tool deformation by cutting forces and chip-tool interface temperature in machining process. Modeling of tool is made using 3D CAD software, finite element method is performed by cutting forces and temperature. Cutting forces and temperature used load conditions are predicted using the cutting force model based on machining theory. Experimental milling tests have been conducted to verify the cutting force model. Finally, this study is predicted cutting force components and temperature using cutting conditions, material property, tool geometry without experiment and tool deformation is predicted by cutting forces and temperature in machining process.