• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.33-39
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• 2007

One of the most important processes is the face milling in processing task. It makes the smooth surface of processed goods. In processing stage, the formation of burr is inevitable. The formed burr decreases a detailed drawing and effects the safety of workers. So, it causes a deburring process for removing and a bottle-neck condition. Therefore, the study which can minimize the generation of burr is needed. In this paper, complex feature, such as line, arc, circle, spline is studied more reality than any other papers. And also, the algorithm which can predict the path of generated burr is established. Moreover, the finality goal is that the system which can produce tool-path minimized has to be developed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1596-1602
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• 2006

대부분의 금형 제작에 있어서 face milling은 가공물의 표면을 매끄럽게 하는 가장 중요한 마무리 공정이다. 이 마무리 단계에서 burr의 형성은 가히 탐탁지 않은 현상중의 하나가 된다. 또한, burr는 가공물의 정밀도를 감소시키고 작업자의 안전에 영향을 미치기 때문에 이를 제거하기 위해 후처리(deburring)과정을 야기 시키며, 불필요한 비용의 발생과 작업의 병목현상을 불러오게 된다. 따라서, burr의 생성 원리를 이해하고 burr의 발생을 최소화 할 수 있는 연구가 필요하게 된다. 이를 바탕으로 deburring의 비용을 줄일 수 있는 최적의 가공계획을 수립해야만 제품의 정밀도를 높일 수 있고, 작업 능률과 생산성을 향상시킬 수 있다. 본 논문에서는 지금까지의 연구보다 좀더 현실적으로 접근하기 위하여 피삭재의 형상이 line, arc, circle, spline 등의 여러 가지 형상으로 복합적으로 이루어진 복합형상에 대하여 burr의 발생을 연구하였고 이에 다중가공 경로까지 고려하여 burr의 형성을 예측할 수 있는 알고리즘을 수립하였다. 더 나아가 본 연구의 궁극적 목적인 burr를 최소로 발생시키는 가공경로를 설계할 수 있는 시스템을 개발하고자 한다

• Journal of the Korean Society for Precision Engineering
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• v.19 no.2
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• pp.133-139
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• 2002

A number of experimental studies on burr formation in face milling operations have been pursued. They usually focus on machining parameters such as depth of cut, leed rate, spindle speed and in-plane exit angle. But it if difficult to set the correlation between burrs and the parameters on burr when such parameters are considered at the same time. Therefore, in this paper, acoustic emission (AE) is considered as an alternate way to predict burr types regardless of machining conditions. AE signals during face milling were sampled and processed, then fed into an artificial neural network to classify burr types \\\"on-line\\\".\\\".uot;.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.12
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• pp.130-136
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• 2001

Burrs formed during face milling operations are very hard to characterize because there are many parameters that affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complex combined effects between the parameters. In this paper, the Taguchi method, which is a systematic optimization application in design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization in face milling. Also, analysis of variance (AVOVA) is employed to study the performance characteristics in more detail. Experimental verifications are provided to show the effectiveness of this approach.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.22-28
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• 2006

Detection of exit burr is very important in manufacturing automation. In this paper, acoustic emission(AE) was used to detect the burr formation during milling. By using wavelet transformation, AE data was compressed without unnecessary details. Then the transformed data were used as selected features (inputs) of a back-propagation artificial neural net. In order to validate the proposed scheme, the wavelet based ANN results were compared with cutting condition(cutting speed, feed, depth of cut, etc.) based ANN results.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.45-52
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• 2006

Burrs formed during face milling operations can be very difficult to characterize since there exist several parameters which have complex combined effects that affect the cutting process. Many researchers have attempted to predict burr characteristics including burr size and shape, using various experimental parameters such as cutting speed, feed rate, in-plane exit angle, and number of inserts. However, the results of these studies tend to be limited to a specific process parameter range and to certain materials. In this paper, the Taguchi method, a systematic optimization method for design and analysis of experiments, is introduced to acquire optimum cutting conditions for burr minimization. In addition, an in process monitoring scheme using an artificial neural network is presented for the prediction of burr types.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.469-473
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• 2003

Milling 가공시 공구와 피삭재의 접합명에서는 절삭가공의 잔유물인 burr가 생성되고, 이러한 Burr는 작업효율과 정밀도를 감소시키며 추처리과정 (Deburring)을 야기시키는 원인이 된다. 그러므로 정밀도와 작업효율을 극대화하기 위해서는 이러한 Burr의 생성원리를 파악함과 동시에 Exit Burr의 여부에 대한 판별을 하여 최적의 가공조건을 맞추어 주어야 하는데, 이러한 경우에 지금까지는 점, 선 및 원으로 피삭재의 형상을 재현하여 공구의 경로와의 Exit 각을 통해 결과를 예측하는 연구를 해왔었다. 본 논문에서 추구하고자 하는 핵심은 이러한 피삭재의 형상을 재현하기 위해 지금까지 사용해왔던 요소를 보다 다양화시키는 방안을 제시하여 프로그램의 적용 범위를 넓히려는 것이다. 예컨대 이제까지 실제 가공에서 사용되고 있는 임의형상에 대한 표현 방식 중에서 대다수 CAD 프로그램에서 곡선 및 곡면을 표현하는 경우, B-Spline Curve의 알고리즘은 패삭재의 불규칙적인 곡면을 가장 근사하게 표현하는 최적의 해결책으로 쓰여지고 있다. 그러므로 이러한 알고리즘을 통해 프로그램의 적용예를 넓히는 것은 보다 다양한 조건에서의 Burr생성에 대한 예측을 가능케 해주는 것이다. 본 논문에서는 앞에서 언급한 바와 같이 B-Spline Curve 알고리즘을 개발하고, 프로그램에 적용하는 일련의 과정을 통해 보다 다양한 형상의 피삭재에서 단일 혹은 복합경로의 공구가 지나갈 경우에 생길 수 있는 Burr를 얼마나 효율적으로 판별할 수 있는지를 소개하고자 한다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.225-229
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• 2000

Burrs formed during face milling operations are very hard to characterize like other machining burrs because there are many parameters which affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complicated combination effects between the parameters. In this paper, Taguchi method, which is a systematic optimization application of design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization. Optimized experimental conditions are provided to show the effectiveness of this approach.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.1
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• pp.134-140
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• 2017

CFRP has many industrial applications due to its low weight and high strength properties. CFRP is a composite material composed of carbon fibers embedded in a polymer matrix; it provides excellent resistance to fatigue wear, corrosion, and breakage due to fatigue. It is increasingly demanded in aircraft, automotive, and medical industries due to its superior properties to aluminum alloys, which were once considered the most suitable for specific applications. The basic machining methods of CFRP are drilling and route milling. However, in the case of drilling, the delamination of each layer, uncut fiber, resin burning, spalling, and exit burrs are barriers to successful application. This paper investigates the occurrence of exit burrs when drilling holes with ultrasonic vibration. Depending on design parameters such as the point angle, the characteristics of hole drilling were identified and appropriate machining conditions were considered.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1172-1182
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• 1993

In orthogonal machining a quantitative model for burr formation process and fracture when tool exits workpiece is proposed. When no fracture during burr formation burr formation process is divided by three parts; Initiation, Development and Final burr formation. According to the properties of workpiece fracture will happen or not after initiation of burr formation. Considering the fact that fracture depends on the ductility of workpiece, the fracture strain obtained from ductile fracture criterion is used for prediction. It is verified that the fracture strain from tension test can be used as fracture criterion in burr formation without large error. For detailed observation of burr formation an experimental stage for micro orthogonal cutting inside SEM (Scanning Electron Microscope) is built. Through the comparison between model prediction and experimental result from orthogonal machining in milling machine the model is verified.