• International Journal of Precision Engineering and Manufacturing
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• 제8권1호
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• pp.16-20
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• 2007

Although conventional contour parallel tool paths obtained from geometric information have successfully been used to produce desired shapes, they seldom consider physical process concerns such as cutting forces and chatter. In this paper, we introduce an optimized contour parallel path that maintains a constant material removal rate at all times. The optimized tool path is based on a conventional contour parallel tool path. Additional tool path segments are appended to the basic path to achieve constant cutting forces and to avoid chatter vibrations over the entire machining area. The algorithm was implemented for two-dimensional contiguous end milling operations with flat end mills, and cutting tests were conducted to verify the performance of the proposed method.

• 한국정밀공학회지
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• 제23권2호
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• pp.35-42
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• 2006

Although the conventional contour parallel tool path obtained from geometric information has been successful to make desirable shape, it seldom consider physical process concerns like cutting forces and chatters. In this paper, an optimized contour parallel path, which maintains constant MRR(material removal rates) at all time, is introduced and the result is verified. The optimized tool path is based on a conventional contour parallel tool path. Additional tool path segments are appended to the basic tool path in order to achieve constant cutting forces and to avoid chatter vibrations at the entire machining area. The algorithm has been implemented for two dimensional contiguous end milling operations with flat end mills, and cutting tests were conducted to verify the significance of the proposed method.

• 한국정밀공학회지
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• 제26권2호
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• pp.133-140
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• 2009

Presented in this paper is a method to generate round-endmill toolpaths for sculptured surfaces represented as a triangular mesh model. The proposed method is applicable in toolpath generation for ball-endmills and flat-endmills because the round-endmill is a generalized tool in three-axis NC (numerical control) milling. The method uses a wireframe model as the offset model that represents a cutter location surface. Since wireframe models are relatively simple and fast to calculate, the proposed method can process large models and keep high precision. Intersection points with the wireframe offset model and a tool guide plane are calculated, and intersection curves are constructed by tracing the intersection points. The final step of the method is extracting regular curves from the intersection curves including degenerate and self-intersected segments. The proposed method is implemented and tested, and a practical example is presented.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.439-444
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• 2004

A new efficient intelligent machining strategy named the Steepest Directed Tree method is presented in this study, which makes surface model discrete with triangulation meshes and the cutter paths track along the tree directions. In order to formulate these algorithms practically, it is deduced the multi-stage machining approach of uncut volume caused by cutter gouging in the course of milling using flat end mill. It is systematized the checking process the cutter interference by grouping the 6 kinds of gouging types, which yields the environment of connectivity data lists including CL-data, and then the multi-stage machining strategy, that minimizes uncut area by continuously sequencing the generative subsequent CL-paths, is shamed to determine the second tool path for the next uncut area and to compose the operating multi-stage cutting processes. The completed machining system of curved surfaces is evaluated by testing the practical machining experiments which have various kinds of shape conditions.

• 한국기계가공학회지
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• 제20권9호
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.