Optimizing tool orientations for 5-axis machining by configuration-space search method
Introduction
5-Axis NC machines are widely used in machining of sculptured surfaces such as aircraft parts, turbine blades, impellers, propellers, 3D cams, molds and dies. Since 5-axis machines have two more degrees of freedom than traditional 3-axis machines, 5-axis machining offers many advantages over 3-axis machining, including better tool accessibility, faster material removal rates and improved surface finish [1], [2]. To make the best use of 5-axis machines, however, we have to solve more complicated interference (gouging and collision) problems and to determine the optimal tool orientations for complex surface machining.
Gouging and tool collision are the main problems in machining sculptured surfaces [3], [4]. As shown in Fig. 1, the cutter interference in 5-axis machining can be classified into three types: local gouging, rear gouging and global collision, according to the interference checking area [5], [6]. Local gouging refers to the removal of the excess material in the vicinity of the cutter contact (CC) point due to the mismatch in curvatures between the tool swept surface and the part surface at the CC point. Several researchers have developed techniques to detect and avoid local gouging by comparing the effective cutting curvature of the tool swept surface to the normal curvature of the part surface at the CC point [3], [7], [8]. As shown in Fig. 1, rear gouging exists when the interference occurs between the bottom of the endmill cutter and the part surface. Global collision is the interference of the cylindrical part of the tool or tool holder and the part surface, including fixtures [1], [3], [9], [10]. Choi et al. [11] proposed a scheme that searched the feasible regions considering the special case of marine propeller machining and minimized cusp heights derived analytically. As for the optimal tool orientation or good positioning issues, many studies are using concepts of differential geometry such as local curvature properties [7], [8], [12], [13]. The curvature-matching schemes have some difficulties handling rear gouge and global collision in a unified manner [1].
Currently, the available commercial CAD/CAM software for 5-axis machining still lacks flexibility when specifying the tool orientation and tool path distribution for complex surface machining [11], [14], [15]. Traditionally the orientation of the endmill has remained fixed during machining. For example, the tool orientation is set to an angle that ranges from 3 to 10° off the principal surface normal during tool motion. Although this approach is demonstrably more efficient than 3-axis sphere-endmill machining [16], gouging and tool collision problems remain, and scallops left on surface need manual grinding and reworking of the machined surface [17], [18], [19]. Although inclining the cutter generally prevents its trailing edge from dragging across the surface, this fixed-orientation method suffers some machining efficiency and gouging problems. These problems are exacerbated when the sculptured surfaces become more complex. The traditional fixed-orientation practice cannot effectively prevent gouging problems during tool path planning for complex surface machining.
Machined surface errors resulting from tool path generation are typically determined using posterior tool path checking and graphic visualization techniques [1], [10], [20]. Although these checking techniques have proven useful in identifying the tool path errors after actual machining, the problems of generating an error-free tool path remain. Currently, intensive user interaction is still needed while using CAD/CAM software to generate NC part programs for sculptured surface machining, which requires considerable checking, verification, and reworking [8], [13], [14]. These problems must be solved so that the full advantages of 5-axis machining can be exploited more widely.
In this paper, we focus on the investigation of a searching method in the machining configuration space (C-space) based on the different machining constraints and a global smoothing method to find the optimal tool orientation for 5-axis machining. We start with a tool path given as a sequence of CC points. We will find at each CC point the orientation of the tool that minimizes cusp height while avoiding gouging and interference. Our method works by considering the parameter space for tool orientations, and finding the region(s) of orientations that avoid gouging and interference. We then find the point within each region that results in minimum cusp height. Key to our method is determining cusp height and detecting gouging/interference. We discuss the former in 3 Machined surface errors analysis for 5-axis machining, 4 Constructing machining configuration space (C-space) and finding the feasible regions and the latter in Section 5. Section 6 presents a complete algorithm of finding the global optimal tool orientations for 5-axis machining, followed by the examples and the concluding remarks.
Section snippets
Tool orientation control in 5-axis machining
In this section, the coordinate systems of 5-axis machining and the cusp height analysis are first introduced and they will be used later in the algorithms for gouging/interference detection. In Fig. 2, the three unit vectors and a CC point rc are used to construct a local orthogonal coordinate frame (f, t, n, rc), called the CC-coordinate system: f denotes the unit vector for the cutter feed direction which is tangent to the surface; n denotes the unit normal vector of the surface; t is a unit
Machined surface errors analysis for 5-axis machining
This section presents the formulation of machined surface analysis during 5-axis simultaneous tool motions, which will be used later in the algorithms of finding the optimal tool orientations. Due to the two additional rotation axes in 5-axis machining, both the cutter location (CL) and the tool orientation need to be determined in cutter path generation. In 5-axis machining, because of the complex tool motion during machining, it is not easy to determine the cutter location (CL) and tool
Constructing machining configuration space (C-space) and finding the feasible regions
In this paper, we are interested in finding the feasible tool orientation for 5-axis finishing of part surfaces without gouging and tool collision. To achieve the mission, we first consider the parameter space for tool orientations and then try to find the region(s) of orientations that avoid gouging and interference. As shown in Fig. 6(a), the local surface surrounding the CC point needs to be checked for possible local gouging and rear gouging, especially at the concave region. As shown in
Finding the optimal feasible tool orientation in the C-space
Fig. 10 shows the flowchart of finding the optimal feasible tool orientation for the given CC paths. Given a CC point CCi in the CC paths, the feasible regions of tool orientation (α,β) in the C-space are first constructed and the local optimal tool orientation is selected. The generated local optimal tool orientations for the CC paths are then processed to find the global optimal tool paths. Two procedures, forward smoothing and backward smoothing, are conducted to find the global optimal tool
Optimal tool path generation by smoothing tool orientation in the C-space
After the feasible tool orientations have been identified for each CC point of the tool paths, problems still exist in multi-axis machining. When the sculptured surfaces are complex, especially for compound surfaces that consist of multiple surface patches, the traditional 5-axis tool path generation methods based on the cusp height minimization cause dramatic tool orientation changes during the actual 5-axis machining. A large angle change of tool orientations between two sequence CC points
Computer implementation and examples
The presented techniques and algorithms have been implemented in a prototype system using C++ programming language on Windows NT personal computers. The input to the system is a polyhedral surface model in STL format. Fig. 12 shows some examples of sculptured surface parts and the tool path generation for machining.
Fig. 13 shows some examples of the feasible regions in the C-space for the example part surfaces. Fig. 13(a) shows a simple concave surface and its feasible C-space region. Due to
Conclusions and future research
This paper presents a geometry analysis and C-space searching method to find the optimal tool orientations for 5-axis sculptured surface machining. Techniques of constructing the machining configuration space (C-space) have been developed to determine the feasible tool orientations by considering local gouging, rear gouging, global collisions and machine limits. Both local and global surface geometries are considered in determining tool orientations for machining. To overcome the common
Acknowledgements
This research was partially supported by the Korea Science and Engineering Foundation through the Research Center for Aircraft Part Technology at Gyeongsang National University. The authors would also like to thank the National Science Foundation CAREER Award (DMI-9702374) and the Army Research Office (Grant #DAAG55-98-D-0003) and to Dr Y.S. Lee at North Carolina State University. Their support is greatly appreciated. The authors would also like to thank the anonymous reviewers for the helpful
Cha-Soo Jun is a professor of Industrial and Systems Engineering, Gyeongsang National University, Jinju, Korea. He received a BS in mechanical engineering from Pusan National University in 1983, and an MS and a PhD, both in industrial engineering from KAIST (Korea Advanced Institute of Science and Technology) in 1985 and 1989, respectively. He stayed at North Carolina State University as a visiting scholar in 2001. His research interests include geometric modeling, sculptured surface machining,
References (30)
- et al.
2-Phase approach to global tool interference avoidance in 5-axis machining
Comput Aided Des
(1995) - et al.
On local gouging in five-axis sculptured surface machining using flat-end tools
Comput Aided Des
(2000) Efficient cutter-path planning for five-axis surface machining with a flat-end cutter
Comput Aided Des
(1999)- et al.
A unified approach to verification in 5-axis freeform milling environments
Comput Aided Des
(1999) - et al.
Cutter-location data optimization in 5-axis surface machining
Comput Aided Des
(1993) Admissible tool orientation control of gouging avoidance for 5-axis complex surface machining
Comput Aided Des
(1997)Non-isoparametric tool path planning by machining strip evaluation for 5-axis sculptured surface machining
Comput Aided Des
(1998)- et al.
5-Axis machining of sculptured surfaces with a flat-end cutter
Comput Aided Des
(1994) Influence of surface shape on admissible tool positions in 5-axis face milling
Comput Aided Des
(1987)- et al.
A shape-generating approach for multi-axis machining G-buffer models
Comput Aided Des
(1999)
Ellipse-offset approach and inclined zig-zag method for multi-axis roughing of ruled surface pockets
Comput Aided Des
Effect of cutter mark on surface roughness and scallop height in sculptured surface machining
Comput Aided Des
Generating 5-axis NC roughing paths directly from a tessellated representation
Comput Aided Des
A new curve based approach to polyhedral machining
Comput Aided Des
Machining potential field approach to tool path generation for multi-axis sculptured surface machining
Comput Aided Des
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Cha-Soo Jun is a professor of Industrial and Systems Engineering, Gyeongsang National University, Jinju, Korea. He received a BS in mechanical engineering from Pusan National University in 1983, and an MS and a PhD, both in industrial engineering from KAIST (Korea Advanced Institute of Science and Technology) in 1985 and 1989, respectively. He stayed at North Carolina State University as a visiting scholar in 2001. His research interests include geometric modeling, sculptured surface machining, CAD/CAM, and CAPP.
Kyungduck Cha is a PhD student in School of Industrial and Systems Engineering, Georgia Institute of Technology. He received a BS and an MS, both in Industrial Engineering, from Gyeongsang National University, Korea in 1997 and 1999, respectively. His research interests include multi-axis NC machining of surfaces, simulation, and application of optimization techniques to medical problems.
Yuan-Shin Lee is an Associate Professor of Industrial Engineering at North Carolina State University, USA. He received his PhD (1993) and MS (1990) degrees from Purdue University, USA, both in industrial engineering, and his BS degree from National Taiwan University, Taiwan, in mechanical engineering. His research interests include CAD/CAM, 3-axis and 5-axis sculptured surface manufacturing, rapid prototyping, computer-aided process planning, and computational geometry for design and manufacturing. He is a registered professional engineer (PE) in mechanical engineering and a certified manufacturing engineer in system integration and control. Dr Lee received the National Science Foundation (NSF) CAREER Award. He also received the 1997 Outstanding Young Manufacturing Engineer Award from the Society of Manufacturing Engineers (SME), the 1998 Norman Dudley Award from the Taylor & Francis Editorial Journals, London, UK, the 1999 Anderson Outstanding Faculty Award and the 2000 Alumni Faculty Outstanding Teaching Award from North Carolina State University, and the 2001 ALCOA Foundation Engineering Research Achievement Award. He serves as an Associate Editor for the Journal of Manufacturing Systems (JMS).
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