• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 추계학술대회 논문요약집
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• pp.80-80
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• 2003

• 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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.717-720
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• 2000

Burr makes troubles on manufacturing process due to of deburring cost, quality of products and automation. 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, we classified the burr type and developed data bases to predict burr formation result. This program will be used to predict burr type and geometry at a specified location. Simulation results on deformation strain and temperature are also available. Also algorithm which calculate the exit angle is proposed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1780-1783
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• 2003

Burrs formed in micro drilling with Ø 1.0 and 0.5 are observed. The changes of burr geometry are compared when feed rate and velocity changes. Characteristics of burr formation in 4 different workpiece materials are analyzed. The coefficient of burr geometry, CB is introduced to classify burrs according to burr height and burr types. Finally control charts are produced using the coefficient of burr geometry and burr types in each workpiece material. Data base is constructed to be used for burr expert system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1110-1113
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• 1995

This study presents the new method which can transfer the expert's skill to deburring robot through neural network. The expert's skill is expressed as associationmapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring processcan be extracted via the visual sense of the human,we employ vision system for the perception and identification of the changing burr. Form the demonstration of human experts, force data are measured. Finally the characteristics of the burr and coressponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• 한국정밀공학회지
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• 제15권9호
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• pp.93-100
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• 1998

This study presents the new method which can transfer the expert's skill to deburring robot through neural network. The expert's skill is expressed as association mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured. Finally the characteristics of the burr and corresponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• 수산해양기술연구
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• 제34권1호
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• pp.1-5
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• 1998

This study presents intelligent deburring system which can transfer the exper's skill to deburring robot through neural network. The expert's skill is expressed as associate mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured and fitted impedance model. Finally the characteristics of the burr and coressponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• 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.

• 한국정밀공학회지
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• 제20권12호
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• pp.25-33
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• 2003

A burr has been defined as undesirable projection of material formed as a 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 this study, the primary interest is about exit burr. The burr formation mechanism in each type of burr is classified. Data bases are developed to predict burr formation result. In the milling operation, we develop an algorithm to analyze the burr formation mechanism by the geometrical analysis on the multi featured workpiece with multi cutting path. The algorithm includes three steps, i. e., the feature identification, the cutting condition identification, and the analysis on exit burr formation. We can predict which portion of workpiece would have the exit burr in advance so that we can manage to find a way to minimize the exit burr formation in an actual cutting. Also, this algorithm can be implemented in a commercial CAM package so that we can simulate the NC code to review the burr formation in advance.

• 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.