• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1816-1819
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• 2003

As a result of milling operation, we expect to have burr at the outward edge of workpiece. Also, it causes undesirable problems such as deburring cost, low quality of machined surface, and bottleneck in manufacturing process. Though it is impossible to totally remove burr in machining, it is necessary to plan a machining process that minimizes the occurrence of burr. In this paper, a scheme is proposed which identifies the tool path of the milling operation with minimum burr. In the previous research, a Burr Expert System was developed where the feature identification, the cutting condition identification, and the analysis on exit burr formation are the key steps in the program. The Burr Expert System predicts which portion of workpiece would have the exit burr in advance so that we can calculate the burr length of each milling operation. Here, the critical angle determines whether the burr analyzed is an exit burr or not. So the burr minimization scheme becomes to minimize the burr with critical angle. By iterating all the possible tool paths in certain milling operation, we can identify the tool path with minimum burr.

• 한국생산제조학회지
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• 제18권4호
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• pp.381-387
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• 2009

The end-milling force behaviour is very complex and it is related to a de-noising phenomenon, so it is very difficult to detect and diagnose this static cutting force phenomenon. This paper presents a new method of filtering of end-milling force in end-milling operation using filter bank technique, based on the wavelet transform. In this paper by comparing the history of end-milling force using wavelet filtering the fundamental end-milling property of the wavelet transform is well reviewed and analyzed. This result of wavelet transform using filter bank shows the possible static prediction of end-milling force with severe dynamic properties such as chatter in end-milling operation.

• 한국공작기계학회논문집
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• 제11권5호
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• pp.100-105
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• 2002

The comprehensive system analysis for contour milling operation and its error has performed in this study. The obtained experimental results were from the practical points of view. In down-milling operation the contour error curve illustrates bigger thean actual workpiece radius. The contour error increased when the cutter loads increased. Through the procedural evaluation, it could ascertain the characteristics of generation mechanics in circular contour machining error, and the weight of each factors.

• 한국CDE학회논문집
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• 제6권4호
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• pp.222-228
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• 2001

In the milling operation, the burr can be generated on the intersection of cutting tool and workpiece. Due to burr formation, we expect lower efficiency in the operation and the cost increase. In order to understand the burr formation mechanism in the milling operation on the arbitrary feature, we developed an algorithm to analyse and predict the exit burr formation mechanism. Firstly, the recognition of arbitrary shaped workpiece was done through the CAD data. This data includes point information on the vertices of the workpiece. Secondly, tile CAM data regarding tool geometry, tool path, cutting speed, and material data are retrieved to simulate the actual cutting process. Thirdly, we predict the exit burr formation on the edge of workpiece based on the geometric analysis. Lastly, an algorithm implemented in the Windows environment to visualize the burr formation simulation. With this information, we can predict which portion of workpiece would have the exit burr in advance so that we call manage to find a way to minimize the edit burr formation in the actual cutting.

• 한국재료학회지
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• 제25권8호
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• pp.386-390
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• 2015

Fe-base superalloy powders with $Y_2O_3$ dispersion were prepared by high energy ball milling, followed by spark plasma sintering for consolidation. High-purity elemental powders with different Fe powder sizes of 24 and 50 mm were used for the preparation of $Fe-20Cr-4.5Al-0.5Ti-O.5Y_2O_3$ powder mixtures (wt%). The milling process of the powders was carried out in a horizontal rotary ball mill using a stainless steel vial and balls. The milling times of 1 to 5 h by constant operation (350 rpm, ball-to-powder ratio of 30:1 in weight) or cycle operation (1300 rpm for 4 min and 900 rpm for 1 min, 15:1) were applied. Microstructural observation revealed that the crystalline size of Fe decreased with an increase in milling time by cyclic operation and was about 15 nm after 3 h, forming a FeCr alloy phase. The cyclic operation had an advantage over constant milling in that a smaller-agglomerated structure was obtained. The milled powders were sintered at $1100^{\circ}C$ for 30 min in vacuum. With an increase in milling time, the sintered specimen showed a more homogeneous microstructure. In addition, a homogenous distribution of Y-compound particles in the grain boundary was confirmed by EDX analysis.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1995년도 추계학술대회 논문집
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• pp.68-75
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• 1995

The milling process is one of the most important metal removal processes in industry. Due to the complexities inherent to the cutter insert geometry and the milling cutter kinematics, these processes leave an analytically difficult to predict texture on the machined surface's hills and valleys. The instantaneous uncut chip cross sectional area may be estimated by the relative position between the workpiece and the cutter inserts. furthermore, since the cutting forces are proportional to the instantaneous uncut chip cross sectional area, the cutting forces in face milling operations can not be estimated easily. A new simulation program which is based upon the numerical method has been proposed to estimate the cutting force components, with the ability to predict the machined surface texture left by the face milling operation.

• 한국정밀공학회지
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• 제19권8호
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• pp.55-62
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• 2002

A burr has been defined as undesirable projection of material formed as the result of plastic flow from a cutting or shearing operation. It is unavoidable in all kinds of machining operation. As a result, burr makes troubles on manufacturing process due to deburring cost, quality of products and productivity. In face milling operation, burrs are formed along five edges on the workpiece. In this study, the primary interest is about exit burr The influence of the cutting parameters on the formation of exit burrs in face milling will be described experimentally. Using the results of experimental study, burr types are classified according to appearance and formation mechanism in exit burr. The burr formation mechanism in each type of burr is suggested. Data bases are developed to predict burr formation result.

• 반도체디스플레이기술학회지
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• 제15권4호
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• pp.86-91
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• 2016

End milling is an important and common machining operation because of its versatility and capability to produce various profiles and curved surfaces. This paper presents an experimental study of the cutting force variations in the end milling of SM25C with HSS(high speed steel) and carbide tool. This paper involves a study of the Taguchi design application to optimize cutting force in a end milling operation. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer resources than a factorial design. This study included feed rate, spindle speed and depth of cut as control factors, and the noise factors were different cutting tool in the same specification. An orthogonal array of $L_9(3^3)$ of ANOVA analyses were carried out to identify the significant factors affecting cutting force, and the optimal cutting combination was determined by seeking the best cutting force and signal-to-noise ratio. Finally, confirmation tests verified that the Taguchi design was successful in optimizing end milling parameters for cutting force.

• 대한기계학회논문집
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• 제16권12호
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• pp.2268-2278
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• 1992

본 연구에서는 기존의 정절삭력 모델을 이용하여 절삭과정에서 발생되는 동적 인 특성과 공작기계의 구조적인 특성이 상호작용되어 발생되는 절삭력 변동성분들이 고려된 절삭력 모델 즉 동절삭력 모델을 개발하여서 이 모델로부터 예측된 절삭력과 절삭실험 결과를 비교, 분석하여 제시한 모델의 타당성 및 동절삭력 특성을 검토하고 자 한다.

• 한국정밀공학회지
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• 제12권12호
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• pp.120-129
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• 1995

This study introduces a tool wear monitoring technology in face milling operation comprised of an unsupervised neural network. The monitoring system employs two types of sensor signal such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are calculated for te input patterns of neural network. ART2 neural network, which is capable of self organizing without supervised learning, is used for clustering of tool wear states. The experimental results show that tool wear can be effectively detected under various cutting conditions without prior knowledge of cutting processes.