• 한국정밀공학회지
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• 제11권5호
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• pp.153-160
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• 1994

In this study, residual stress and surface roughness were investigated experimentally to evaluate surface integrity on surface layer machined by CBN, ceramics and WC cutting tools. When machining difficult-to-cut material (hardened STD11 steel $H_{R}$C 60), residual stresses remaining in machined surface layer were mainly compressive. The increase of flank wear caused a shift of the compressive residual stress maximum to greater workpiece depths, but the changes did not penetrate the workpiece beneath a depth of 300 .mu. m. Surface roughness was influenced considerably by variations of the cutting speed and feed. In machining hard material, CBN and A1$_{2}$ $O_{3}$ ceramics cutting tool materials proved significantly superior to mixed ceramics A1$_{2}$ $O_{3}$-TiC and WC in evaluation of surface integrity.y.

• 한국정밀공학회지
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• 제16권4호통권97호
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• pp.220-228
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• 1999

The machining accuracy has been improved with the development of NC machine tools and cutting tools. However, it is difficult to obtain a high degree of accuracy when machining deep pocket with long end mill, since machining accuracy is mainly dependant on the stiffness of the cutting tool. To improve surface accuracy in machining deep pocket using end mill, the performance by down cut and up cut is compared theoretically and experimentally. To verify usefulness of up milling, various experiments were carried out. As a result, it is found that up milling produce more accurate surface than down milling in machining deep pocket. For effective application of up milling, various values in helix angle, number of teeth, radial depth of cut and axial depth of cut are applied in experiment.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.315-319
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• 1999

This paper has been considered on the cutting characteristics such as chip formation and surface roughness for Inconel 690 alloy with difficult-to-cut because of high toughness and strength. We have made efforts solving the problem to difficult-to-cut of Inconel by improvement of tool with TiN coating and the selection of optimum cutting condition. We used the CCD camera and the surface roughness tester to observe the chip formation and the state of machined surface by using the improved tool with diamond coating and various cutting condions. We have found that the chip formation showed the tooth shape of tooth blade and the surface roughness was very poor. but it can be better by selection of optimum cutting condition.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.266-269
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• 2002

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. For this study, the micro-grooving machine was developed. The experiments were performed using diamond blade and CBN blade f3r machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied.

• Agricultural and Biosystems Engineering
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• 제1권2호
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• pp.100-105
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• 2000

Quality sorting of cut flowers is very essential to increase the value of products. There are many factors that determine the quality of cut flowers such as length, thickness, and straightness of stem, and color and maturity of bud. Among these factors, the straightness of stem and the maturity of bud are generally considered to be more difficult to evaluate. A prototype grading and sorting machine for cut flowers was developed and tested for a rose variety. The machine consisted of a chain-drive feed mechanism, a pneumatic discharge system, and a grading system utilizing color image processing and neural network. Artificial neural network algorithm was utilized to grade cut roses based on the straightness of stem and maturity of bud. Test results showed 89% agreement with human expert for the straightness of stem and 90% agreement for the maturity of bud. Average processing time for evaluating straightness of the stem and maturity of the bud were 1.01 and 0.44 second, respectively. Application of neural network eliminated difficulties in determining criteria of each grade category while maintaining similar level of classification error.

• 한국공작기계학회논문집
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• 제11권2호
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• pp.87-94
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• 2002

In domestic industry, there is no manufacturers specialized in the production of cutting tools for the difficult cutting materials. Then, we have flew data about them. In this study, the gear driving high speed lathe on which is mounted by a tool dynamometer and high speed CCTV were used to measure the various machining characteristics. Relations among the cutting speed, feed rate per revolution, cutting depth, cutting forces and surface roughness ware graphically analyzed under 64 cutting conditions. The process of chip, i.e., generation, development and falling-off also were visualized for the characterization of chip shapes of the difficult-to-cut materials using the CCTV.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.951-954
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• 2000

This paper presents a new cutting method, i.e. diamond cutting, aided by electrolysis, in order to cut ferrous materials with diamond tools. Diamond cutting is widely applied in manufacturing ultraprecision parts such as magnetic disk, polygon mirror, spherical/non-spherical mirror and copier drum, etc. because of the diamond tool edge sharpness. In general, however, diamond cutting cannot be applied to cutting steels, because diamond tools wear excessively in cutting iron based materials like steel due to their high chemical interaction with iron in high temperature. In order to suppress the diffusion of carbon from the diamond tool and to reduce increase of cutting force due to size effect, we attempt to change chemically the compositions of iron based materials using electrolysis in a limited part which will be soon cut. Through experiments under several micro-machining and electrolysis conditions, cutting using electrolysis, compared to conventional cutting, was found to result in a great decrease of the cutting force, a better surface and much less wear tool.

• 한국생산제조학회지
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• 제25권1호
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• pp.83-88
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• 2016

Because of the increasing tool cost for cutting hard-to-cut materials, abrasive water jet (AWJ) milling recently has been regarded as a potential alternative machining method. However, it is difficult to control the depth and width of cut in AWJ milling because they vary depending on many AWJ cutting parameters. On 27 conditions within a limited range of pressure, feed rate, and abrasive flow rate, AWJ cutting was conducted on titanium, and depth profiles were measured with a laser sensor. From the depth profile data, depth and width of cut were acquired at each condition. The relationships between depth and parameters and between width and parameters were derived through regression analysis. The former can provide proper cutting conditions and the latter the proper pick feed necessary to generate a milled surface. It is verified that pressure mostly affects depth, whereas abrasive flow rate mostly affects width.

• 한국지반공학회논문집
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• 제24권2호
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• pp.37-44
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• 2008

절취사면의 붕괴는 지질 및 지형적인 요건과 수리적인 요건 등 매우 다양한 요인들이 복합적으로 작용하여 발생한다. 그러나 현행 절취사면의 사전 및 사후 유지관리 단계에서 복잡한 지질조건에 따른 안정성 저해에 미치는 영향을 평가함에 있어 매우 미흡한 실정이다. 본 연구에서는 국내 유지관리 주체별 현황 및 암종별 붕괴 특성 및 유지관리 사례분석 등을 실시하고 이를 통하여 암종별 특성이 고려된 국내 절취사면의 유지관리 방안을 제시하고자 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.18-22
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• 2004

It is difficult to understand a person's emotion, since it is subjective and vague. Therefore, we are proposing a method by which will effectively classify human emotions into two types (that is, single emotion and composition emotion). To verify validity of te proposed method, we conducted two experiments based on general inference and $\alpha$-cut, and compared the experimental results. In the first experiment emotions were classified according to fuzzy inference. On the other hand in the second experiment emotions were classified according to $\alpha$-cut. Our experimental results showed that the classification of emotion based on a- cut was more definite that that based on fuzzy inference.