• 한국정밀공학회지
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• 제18권12호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.1000-1003
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• 2001

This paper presents the numerical analysis and experimental verification to know the metal cutting burr formation mechanism in face milling operation. Finite element method are applied to predict the 2-D burr formation process prediction. Face milling process are adjusted to analyze the characteristics of burr shapes according to various cutting conditions. The cutting parameters were investigated with cutting speed, feed rate, depth of cut. Through the experiments various burr types are classified according to its shape and properties.

• 한국공작기계학회논문집
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• 제15권4호
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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.

• 한국공작기계학회논문집
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• 제16권1호
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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.

• 한국공작기계학회논문집
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• 제15권3호
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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.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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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

• 한국정밀공학회지
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• 제18권2호
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• pp.199-205
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• 2001

Burr makes troubles on manufacturing process due to deburring cost, quality of products and productivity. This paper described the results of experimental study on the influence of the cutting parameters on the formation of exit burrs in face milling. Using the results of experimental study, burr types are classified and data bases are developed to predict burr formation result. From the CAD file for work geometry and the NC data for tool path, the exit angles are calculated at every edges. This program predicts the burr geometry at exit edges using the prediction algorithm and data bases which are developed experimentally. Simulation results on deformation strain and temperature are also available in specific 2-dimensional cutting conditions. Also algorithm which can determine the exit angle is proposed.

• 산업경영시스템학회지
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• 제23권60호
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• pp.23-36
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• 2000

A probabilistic model of burr formation in face milling of gray cast iron is proposed. During a face milling operation, an irregular pattern of the edge profile consisting of burrs and edge breakouts is observed at the end of cut. Based on the metal cutting theory, we derive a probabilistic model. The operational bayesian modeling approach is adopted to include the relevant theory in the model.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 추계학술대회논문집 - 한국공작기계학회
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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.

• 산업공학
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• 제18권3호
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• pp.247-252
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• 2005

In the automated production environment in the present days, the minimization of manual operation becomes a very important factor in increasing the efficiency of the production system. The exit burr produced through the milling operation on the edge of workpiece usually requires manual deburring process to enhance the level of precision of the resulting product. So far, researchers have developed various methods to understand the formation of exit burr in cutting process. One method to analytically identify the formation of exit burr was to use the geometrical information of CAD and CAM data used in automated machining. This method, in turn, generated the information resulting from the analysis such as burr type, cutting region, and exit angle. Up to now, the geometrical data were restricted to the single feature and single path. In this paper, a method to deal with the complicated geometric features such as line segment, arc, hole, and spline will be presented and validated using the field data. This method also deals with the complex workpiece shape which is a combination of multiple features. As for the cutting path, multiple tool path is analyzed in order to simulate the real cutting process. All this analysis is combined into a Windows based software and real data are used to validate the program in the conclusion.