• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.2 s.179
• /
• pp.35-42
• /
• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.10a
• /
• pp.3-6
• /
• 2002

This paper presents the cutting simulation system for prediction and regulation of cutting force in CNC machining. The cutting simulation system includes geometric model, cutting force model, and off-line fred rate scheduling model. ME Z-map(Moving Edge node Z-map) is constructed for cutting configuration calculation. The cutting force models using cutting-condition-independent coefficients are developed for flat-end milling and ball-end milling. The off-line feed rate scheduling model is derived from the developed cutting force model. The scheduled feed rates are automatically added to a given set of NC code, which regulates the maximum resultant cutting force to the reference force preset by an operator. The cutting simulation system can be used as an effective tool for improvement of productivity in CNC machining.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.2 s.95
• /
• pp.234-243
• /
• 1999

Using the geometric and the vector methods, three dimensional surface texture and roughness models in flat end milling are developed. In these models, rear cutting effect on surface generation is considered along with tool run-out and tool setting error including tool tilting and eccentricity between tool center and spindle rotational center. Rear cutting is the secondary cutting of the already machined surface by the trailing cutting edge. The effects of tool geometry and tool deflection on surface roughness are also considered. For representing the surface texture more practically, three dimentional surface topography parameters such as RMS deviaiton, skewness and kurtosis are introduced and used in expressing the surface texture characteristics. Under various cutting conditions, it is confirmed that the developed models predict the real surface profile precisely. These models could contribute to the cutter design and cutting condition selection for the reduction of machining and manual finishing time.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.19 no.2
• /
• pp.251-259
• /
• 2010

It is presented in this study a new efficient intelligent machining strategy, which can be used to remove the uncut volume at the boundary region of curved surfaces caused by cutter interference. The geometric form definitions and recognition of topological features of the surface triangulation mesh are used to generate cutter paths along successive and interconnected steepest pathways, that minimize the cusp height left after flat end milling. In order to machine the uncut volume gradually, the z-map cutter centers are adjusted to avoid cutter interference for the 6 kinds of avoidance types. And then, the generative subsequent paths are sequenced to determine the second step cutter paths for the next uncut volume. For the 2 kinds of test models with convex and concave surface region, the implemented software algorithm is evaluated by investigating the residual swelling of uncut volume for each machining step.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.25 no.3
• /
• pp.399-407
• /
• 2001

The Surface, generated by end milling operation, is deteriorated by tool runout, vibration, friction, tool deflection, etc. Especially in cornering cut, surface accuracy is usually determined by varying cutting forces, which causes tool deflections. Cutting conditions like feed rate is usually kept constant during machining a part, which causes dimensional error in severe cutting. Cornering cut is a typical example of deterioration of surface accuracy when constant feed rate is applied. Therefore it becomes important to develop NC post processor module to determine optimal cutting conditions in various cutting situations. In this paper, cutting force is predicted in cornering cut with flat end mill and feed rate is determined by constraining constantly resultant force. Also some control characteristics of CNC machining center are evaluated.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.2
• /
• pp.133-140
• /
• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.10a
• /
• pp.439-444
• /
• 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.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.9
• /
• pp.90-96
• /
• 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.