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The paper presents a tool path generation methodology for roughing operation based on the oriented graph theory. The cutting areas are identified using an original method that is based on a bicolor and binary map. The toolpath is generated using the searching Dijkstra algorithm inside a graph in order to find the single-source shortest path. The method was employed in order to be applied on ordered and/or unordered point clouds. The entire algorithm was implemented into a mathematic calculus solution which allows the import of point clouds and its processing until the final NC code is generated.
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Procedia CIRP 25 ( 2014 ) 75 80
Available online at www.sciencedirect.com
2212-8271 © 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/3.0/).
Peer-review under responsibility of The International Scientific Committee of the 8th International Conference on Digital Enterprise Technology - DET
2014 – “Disruptive Innovation in Manufacturing Engineering towards the 4th Industrial Revolution”
doi: 10.1016/j.procir.2014.10.013
ScienceDirect
8th International Conference on Digital Enterprise Technology - DET 2014 “Disruptive Innovation in
Manufacturing Engineering towards the 4th Industrial Revolution
Direct toolpath generation based on graph theory for milling roughing
Daniela Popescua, Florin Popistera*, Sorin Popescua, Calin Neamtua, Mircia Gurzaua
Technical University of Cluj-Napoca, Blvd. Muncii 103-105, Cluj-Napoca, 400641, Romania
* Corresponding author. Tel.: +40 742 394980. E-mail address: florin.popister@muri.utcluj.ro
Abstract
The paper presents a tool path generation methodology for roughing operation based on the oriented graph theory. The cutting areas are
identified using an original method that is based on a bicolor and binary map. The toolpath is generated using the searching Dijkstra algorithm
inside a graph in order to find the single-source shortest path. The method was employed in order to be applied on ordered and/or unordered
point clouds. The entire algorithm was implemented into a mathematic calculus solution which allows the import of point clouds and its
processing until the final NC code is generated.
© 2014 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the Scientific Committee of the “8th International Conference on Digital Enterprise Technology - DET
2014.
Keywords: direct toolpath, graph theory, cloud points, roughing
1. Introduction
More and more researchers are studying the problem of
direct tool path generation from point clouds because the
devices capable of creating such geometry are becoming more
efficient. These point clouds can be generated by 3D scanning
of a real object (contact or non-contact) using Computer
Tomography (CT) or by using photogrammetry.
Machining toolpath generation directly on point cloud
shortens the reverse engineering cycle of a component and
can reduce costs by eliminating the scan processing costs.
Thus, the filtering stage, the mesh generation stage and the
surface generation stage can be completely eliminated.
Usually the software of the scanning equipment (either by
palpation, or laser, or optical) allows a primary processing of
the point cloud so that it can be filtered or cropped to remove
unwanted points.
As show in [1], rapid generation of contour from massive
point cloud data is the crucial step for feature-based model
reconstruction. Based on the outline of a point cloud a clear
distinction can be made between the area where the material
is to be chipped and the area where it must remain intact.
In [2] the authors propose an algorithm for generating
roughing and finishing tool paths on measured data directly
by using Moving Least-Squares (MLS) method. In their
algorithm the roughing is performed in a slice-by-slice
manner to remove material rapidly. They generate an offset
point cloud for machining allowance, and slicing data points
were fitted by using MLS method to generate offset curve for
ball-end cutter.
Using the same technique for slicing the cloud point in
order to extract the machining regions (contour curves and
their inclusion relationships), [3] uses a boundary extraction
algorithm for determining the machining region. To avoid the
computational difficulties, they develop an algorithm to
calculate the finishing tool-path based on well-known 2D
geometric algorithms, such as 2D curve offsetting and
polygonal chain intersection algorithms.
In [4] the authors present a strategy for direct tool path
generation based on B-spline surfaces constructed using
extracted point data form initial cloud as control points. They
generate the adaptive (region-based) tool paths that overcome
the inherent drawback (redundant tool paths).
© 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/3.0/).
Peer-review under responsibility of The International Scientifi c Committee of the 8th International Conference on Digital Enterprise
Technology - DET 2014 – “Disruptive Innovation in Manufacturing Engineering towards the 4th Industrial Revolution”
76 Daniela Popescu et al. / Procedia CIRP 25 ( 2014 ) 75 – 80
In [5] the authors present a method based on generating
iso-planar piecewise. The primary direction of the generated
iso-planar tool paths is derived from the projected boundary
of the discrete points. A projected cutter location net (CL-net)
is then created, which groups the data points according to the
intended machining error and surface finish requirements.
In [6] a point-based conformal map is employed to build
the parameterization cloud point based on discrete Laplace
equation. They use also Iso-parametric curve determined in
base of normal curvature.
Surfel is the term used by [7] to describe the association of
“surface” and “element” in an entity which is used for
rendering the scanned data. Direct tool path generation is
made using a point-based model which is created using an
elliptical Gaussian re-sampling filter that is based on a signal
re-sampling algorithm. They use a re-sampling filter based on
Nyquist criterion to transform the input data (random cloud
point) into a continuous surface and then re-sample the
continuous surface. Because the re-sampled data can
accurately represent the original surface, tool paths can be
generated using CL. The CL point is found by lowering the
cutter in the direction normal to the projection plane until
contacts with the re-sampled points are made.
Using an algorithm based on 3D biarc fitting technique it is
possible to generate a 5-axis machining tool-path as shown in
[8]. They construct a three-dimensional (3D) triangular mesh
from the digitizing data with the mesh points considered as
the tool contact locations. The tool axis orientations which
must be determined in 5-axis tool-path are calculated using
3D biarc fitting.
[9] Since such planning falls into the iso-parametric
category, it intrinsically depends on the parameterization of
point clouds. Accordingly, a point-based conformal map is
employed to build the parameterization. Based on it, formulas
of computing path parameters are derived, which are much
simpler than the conventional ones. By regularizing parameter
domain and on the basis of the previous formulas, boundary
conformed tool-path can be generated with forward and side
step calculated against specified chord deviation and scallop
height, respectively. Experimental results are given to
illustrate the effectiveness of the proposed methods.
As shown in the literature, it has not been reported yet any
research aimed directly at tool path generation based on graph
theory. The majority of developed methodologies use slicing
and various algorithms and methods to reduce the number of
points and to generate the tool path.
2. Methodology for Direct tool path generation in case of
roughing
Current digitization technology allows scanning free form
type surfaces and directly obtaining the point cloud, Fig. 1, or
in some cases directly obtaining the 3D meshes [10, 11].
The algorithm presented in this paper can be applied in
case of roughing and finishing with commercial milling tools
in case of both ordered point clouds and unordered point
clouds.
Fig. 1. Ordered point cloud (top) and unordered (bottom)
Fig. 2. General algorithm
Starting from the point cloud direct tool path generation is
done by following the steps below (Fig. 2):
1. Alignment of the point cloud: its orientation in space,
establishing the axes system and determining the upper
and lower limits on the Z axis.
2. Cloud segmentation on Z axis: it is done by slicing on
perpendicular planes to the Z axis, the slicing pitch is
determined taking into account the parameters of the
cutting operation (tool geometry, material, feed rates,
etc.) and the geometry of the component that will be
cut.
3. Point recovery: beginning with the second segmentation
plane all points that are found above the sectioning
plane in which the tool path is calculated are projected
on that plane from top to bottom. This operation aims to
77
Daniela Popescu et al. / Procedia CIRP 25 ( 2014 ) 75 – 80
use all points to generate the tool path correctly and to
avoid collisions with already chipped areas
4. Cloud segmentation on XY plane: for each layer
obtained from the previous operation a grid is made. It
will be generated starting from the x=0 and y=0 point.
The lines and columns of the grid that bound the point
cloud contour are doubled in order to generate a
trajectory that allows correct processing of the contour.
5. Identify the milling area: the grid defined at 3 is
individually analyzed and each unit is assigned a value
of 1 if it contains points (red color) and 0 if it doesn’t
contain points (white color). This step takes into
account both points belonging to the slicing plane and
those obtained at 4 point recovery.
6. Direct tool path generation: using the properties of
oriented graphs the toolpath is generated.
To illustrate the mathematical apparatus and the
implementation of the processing algorithms, a free form type
Bèzier surface was generated, Figure 3, which was later
physically materialized and scanned to obtain ordered and
unordered point clouds. The surface was generated using the
equation:
ܾݑǡݒσσଵଶ
൯ቀଵଶ
ଵଶ
௝ୀ଴
ଵଶ
௜ୀ଴ ݑͳെݑଵଶି௜ݒͳെݒଵଶି௝ܽ௜ାଵǡ௝ାଵ (1)
where ݑאͲǡͳǡݒאͲǡͳ
The points’ coordinate matrix was generated to obtain a
Bézier surface having a complex free form type geometry
which contains peaks and valleys and a caldera. According to
the methodology, which is focused on processing complex
surfaces using three axes milling machines, the surface was
mathematically modelled so that it does not contain
overhangs, i.e. a line parallel to the Z axis must intersect the
surface at one point. The set of parameters was chosen so that
the generated surface fits into a 50 mm side square.
Fig. 3. Bèzier surface used as a standard
The surface was machined on a milling machine and then
scanned using contact and noncontact scanning equipment to
obtain ordered (47817 points) and unordered point clouds
(196057 points).
When machining complex surfaces using 3-axes CNC
machines, the tool path can be described generally as a
function of two variables:
ݖൌ݂ݔǡݕ (2)
The point cloud can be described by the equation:
ܽൌݔݕݖ
ݔݕݖ
ݔݕݖอ (3)
If we make the following notations:
ܾݔൌอݔ
ݔ
ݔǢܾݕൌอݕ
ݕ
ݕǢܾݖ
ݖ
ݖ (4)
Then, to determine the workspace, we will determine the
maximum values of the vectors bx, by and bz.
In order to optimize the trajectory calculation, the first step
is to create segmentation on the Z axis, thus obtaining planes
parallel to the XOY plane as shown in Figure 4.
Fig. 4. Sectioning the cloud point
Setting then slicing pitch is based on quality of the
geometry of the machined surface, quality of the point cloud
(density, ordered, etc.), milling speed, quality of the milled
material, etc. For proper results the authors recommend that
the distance between the sectioning planes (dz) is not greater
than:
݀ݖൌ݀כͲǤ͵Ͷ
Τ (5)
where d is the diameter of the mill.
To determine the number of planes with which the cloud
point is sectioned on the Z axis, it must not be a fractionary or
mixed number, thus the integer will be extracted from the
following mathematical expression:
݊ൌ೘ೌೣି௭೘೔೙
(6)
where, zmax, zmin represent the minimum and maximum
values of the matrix b, dz represents the distance (depth of
cut) between the planes determined with formula 5.
If the result of equation 5 is not an integer then it is
rounded positively, the counting of the section planes begins
with zmin. The section planes are denoted with zi where ziܰכ .
Point recovery
The third step of the algorithm is the point recovery, Figure
5, it involves the projection of all points that are found above
78 Daniela Popescu et al. / Procedia CIRP 25 ( 2014 ) 75 – 80
a sectioning plane. The projection of the points from the upper
layers (from Zmax to Zmin) enables rapid determination of tool
paths through the oriented graphs method taking into account
the upper layers already machined. This operation is done by
changing the Z coordinate of the points that are above the
current sectioning plane. The projection is done on the
sectioning planes beginning with the sectioning plane at zmax.
Fig. 5. Point recovery
The identification of the points is made by comparing the
point’s Z coordinate with the height of the sectioning plane.
The index function for each layer is defined, which is 0 if
the layer doesn’t have any points and it receives the value 1 if
there are points in the layer.
For each point a[[j]] ( j gets values from 1 to Np = number
of points) is calculated (i = the smallest integer higher or
equal to (the difference between the maximum value z1 and
the value of the point a[[j,3]]) divided at the height of a layer
(dz) and if this number is 0, then the value 1 is assigned:
݅ൌቒ௭ଵି௔ሾ௝ǡଷ
ௗ௭ ቓǢܫ݂ሾ݅Ͳǡ݅ൌͳ; (7)
Cloud segmentation on XY plane
To determine the milling area, the oriented graph theory is
used. In the first phase a constant pitch grid, Figure 6, is
generated on both axes (x and y), the size of two grid lines
can be approximated as being equal to the radius of the mill.
In the second phase it identifies the areas of the grid where
points are found. This is done by comparing each point in that
layer with a series of discrete values representing the grid
Fig. 6. Creating the grid
nodes. In this operation are taken into account all the points
obtained after the recovery operation as can be seen in the
figure below.
Each space in the grid that contains at least one point is
numbered 1 (red) and will be part of the area that will not be
machined for that layer. Spaces containing no points are
numbered 0 (white) and will be part of the area for which the
milling trajectory will be determined as shown below.
Using tandem numbering and coloring enables the creation
of a binary and bi-color map, Figure 7, whose nodes are used
to generate the trajectory.
Fig. 7. Binary and bi-color map
Direct tool path generation
Trajectory calculation is made based on the contact point,
CC point, which can be found on the grid. The distance
between the grid lines was chosen to be ½ of the milling
tool’s diameter, thus allowing the use of different milling
geometries using a single algorithm: oriented graphs theory.
Define the following oriented graph:
ܩൌܺǡܷ (8)
where X is the set of vertices, in our case represented by
the set of grid nodes, and U is the set of arcs, represented in
our case by the set of points.
Thus any arc u Є U will be represented through
ݑൌݔǡݕݓ݄݁ݎ݁ݔǡݕאܺݏ݅ݔݕ (9)
To determine the trajectory of the milling tool the chain
sequence of arcs:
ܥൌݑǡݑǡڮݑ (10)
With the condition that any arc ui from this array shares an
extremity with ui-1 , and the other extremity is shared with ui+1
for any i=1,...,n-1.
If all the arcs from the same L chain have the same
orientation that is given by direction from x0 to x
n then the
chain is called a road.
The road in an oriented graph G(X,Y) is an array of peaks:
ܶൌݔǡݔǡڮݔ (11)
With the property that (x0, x1), (x1, x2), ….,(xn-1, xn) Є U
(are arcs of the graph G).
The peaks x0 and xr are called extremities of the road D. If
the peaks x0 ,x1 , ... , xr are distinct, the road D is called
elementary. Thus, an oriented graph G is called connected if
79
Daniela Popescu et al. / Procedia CIRP 25 ( 2014 ) 75 – 80
for any two distinct peaks x and y there is a chain of
extremities x and y in G.
In order to determine the shortest path in an oriented graph,
one can use Dijkstra’s algorithm or the Roy-Floyd algorithm.
Dijkstra’s algorithm is a search in a graph algorithm that
solves the single-source shortest path problem for a graph
with non-negative edge path costs, producing a shortest path
tree [12].
Generating the peaks, v, of the grid using the resulted grid
is achieved determining the indexes of the points that can be
touched by the milling tool generating minimal paths in order
of increasing lengths.
After determining the shortest path to the area that will be
machined (the graph that contains type 0 or white nodes) the
scallop area between two successive passes of spherical
geometry mills is calculated based on the formula below:
ܰሾሼʹܥ݋ݏሾݐሿǡʹʹܵ݅݊ሾݐሿሽȀǤݐ ՜ܲ݅ ͵
Τ
(12)
ሾሼʹܥ݋ݏሾݐሿǡʹʹܵ݅݊ሾݐሿ
ൌሼʹ൅ʹܥ݋ݏሾ߬ሿǡʹʹܵ݅݊ሾ߬ሿሽǡሼݐǡ߬ሽሿ
where N-forms the spherical profile
results
ሼሼݐ՜
ǡ߬՜ଶగ
ሽǡሼݐ ՜
ǡ߬՜ଶగ
ሽሽ (13)
3. Validation
The surface of Figure 8 was machined on CNC equipment
and it was validated in terms of shape deviations by point by
point measuring and comparing with the CAD model using a
multisensor CMM. After the validation, the surface was
digitized, Figure 9, using the contact and non-contact methods
in order to obtain ordered and unordered point clouds (Figure
1).
Fig. 8. Machined standard surface
After the digitization the ordered cloud point contains
47817 points while the unordered one contains196057 points.
For the segmentation on the Z axis a pitch of 0.5 mm was
chosen, that corresponds to the depth of cut, thus resulting 25
layers.
The distance between two consecutive trajectories is ½ of
the milling tool’s diameter, for validation two types of milling
tools were used: ball mill and end mill having diameters of 4
mm with two cutting areas (flutes).
After calculating the trajectory, the NC program is
generated directly in Mathematica according to the
requirements of ISO 6983-1 regarding program format and
definitions of address words.
Using the same parameters for segmentation (both Z axis
and the plane XOY) 36763 program lines were obtained in
case of the ordered point cloud and 38411 lines in case of the
unordered point cloud.
Fig. 9. Equipment used to digitize the master part: contact scanning
equipment (up) and multisensor measuring and scanning equipment (down)
The Figure 10 shows the result of machining with two
different mills (a, b, c and d) in case of using a distance of ½
of the milling tool’s diameter between the trajectories and
constant machining allowance.
Ball end mill
End mill
Roughing based on an ordered cloud using
a) using ball end mill
b)using end mill
Roughing based on an unordered cloud using
c) using ball end mill
d) using end mill
Fig. 10. Results of milling with different cutting tools
80 Daniela Popescu et al. / Procedia CIRP 25 ( 2014 ) 75 – 80
To validate the algorithm and the work method, the
machining process was continued in order to obtain the
finished masterpart. Thus, based on the roughing algorithm,
the finishing methodology was developed using broadly the
same concept and tool support (Mathematica).
The differences between the two procedures (roughing and
finishing) are described below.
To obtain the trajectory for the finishing operation in case
of using the ordered point clouds, the procedure is the
following:
1. The alignment of the point cloud: see roughing
operation
2. Cloud segmentation on Y axis the point cloud is
sliced in the plane XOZ with a minimum pitch of 0.1 mm
3. Establishment of Control Points: the identification of
which points will be taken into account when generating the
toolpath
4. Direct tool path generation: generating the offset
trajectory using Bezier curves and using CL (Cutter Location)
In case of the unordered cloud points, Control points are
established using the following algorithm:
Dividing the machined area into 0.2 mm side
squares, the intersection of each of the squares’ diagonals will
be a control point for the Bezier curve
Check that in the set of points within the square there
is a point which coincides with the intersection of the
diagonals: if there is, it becomes a control point; if there isn’t,
the Z coordinate of the intersection of the diagonals is
determined using all the points belonging to the cloud point
which can be found in a 5x5 matrix centered on the square for
which the z coordinate is determined.
After the final machining operation, the master part was
scanned and compared to the initial 3D model. The
differences are highlighted in the color map, Figure 11.
Fig. 11. Deviation analysis between CAD model and machined surface in
case of: ordered cloud point (up) and unordered cloud point (bottom)
4. Conclusions
Direct tool path generation using the oriented graphs’
properties is the first approach in literature as was shown in
the introduction to this article and allows rapid generation of
machining trajectories based on an algorithm that computes
the shortest path between two vertices.
The presented working methodology has been
implemented in a mathematical program for general use and
has been validated on the surface of a master part generated
by a mathematical equation (1). For the validation process
even the finishing operation was done using a methodology
derived from the roughing process in order to be able to
compare the master part with the CAD model using a
multisensory CMM.
The presented methodology can be used both for ordered
and unordered cloud points. Even though between the number
of points there is a difference of four times, the number of
lines of the NC program is about equal, however at this time
the NC program has quite many lines. Using the oriented
graph proprieties the interference that can appear during tool
path generation process directly from measured or scanned
data points allows generating the shortest path provides a
trajectory optimization to minimize air movement of the
milling tool. The method for identifying the area to be
machined is original and highlights for the first time in binary
and bicolor map the areas that will generate the toolpath. Even
if the implementation in Mathematica enables automatic
generation of NC code, the number of program lines is very
large; this should be optimized in future.
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Nature is an excellent source of inspiration. Understanding nature can lead to new discoveries of new materials, applications, products. Scientists have found out technologies that seek to mimic some of life's unique innovations. In Germany researchers have developed a synthetic shark skin made of elastic silicone that reduces bio‐fouling. Engineers from the Massachusetts Institute of Technology have developed some “biomimicry” material out of glass and plastic that collects minute amounts of water, just like the Namib Desert beetle's back. Polymer composites are used for a very good replication of the mold cavities surface microstructures. Transformation of image to surface could be an economical solution for machining the injection mold cavities for mimic the inspiration source. In this paper an algorithm for combining the tool paths obtained on an image‐to‐surface technique with the tool paths on a complex shaped cavity is presented. The algorithm is tested by micro‐milling an injection mold surface of a cavity for a scale model stone wall and the injection molding experiments have proven the high quality of detail replication.
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Complex industrial parts such as dies and molds are produced on multi-axis CNC machines. Efficiency and utilization of such machines are dictated to a great extent by the availability of efficient part programs to carry out various roughing and finishing operations. This paper presents a novel approach for the tool path planning of roughing operation of complex machining features using voxelization. The developed system takes the CAD part model in STL format as the input. Machinable and non-machinable regions are identified using voxelization followed by the generation of isoplanar zig-zag roughing tool path for 3-axis milling machine. The system was tested for different parts with varying complexities. The developed voxel-based tool path strategy was found to be generic, computationally efficient, and productive compared to those in commercial software.
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The reverse engineering process has been used in the last years in different industrial applications in order to reproduce existing parts on many accounts. A specific feature of the process is getting the CAD model of the existing part based on the digitized data that results from the 3D scanning processes. The digitized data are represented through a point cloud that defines the topology of the initial scanned part. This paper presents a case study through which is obtained on a three axis CNC milling machine tools the mould of a ceramic handmade tile directly from the point cloud. In this direction the approach assumes the elimination of several specific steps of the reverse engineering concept: processing the point cloud and the CAD modelling in order to reduce the numbers of specialized engineers involved in the entire process and the number of dedicated software's.
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Rapid generation of contour from massive point cloud data is the crucial step for feature-based model reconstruction. This paper proposes a fast contour generation algorithm of massive point cloud data based on slicing. To extract the featured points (FPs) from slice, a layer-based point cloud model is directly generated from the point cloud data and serves as the input of a digital image based method. Meanwhile, the size of the grid of digital plane is discussed for fast getting FPs. Based on the FPs of each slice, bidirectional index connecting method (BICM) is put forward to quickly construct layer contour. Finally, the curve model is generated. Several case studies are presented to illustrate the efficiency and accuracy of this approach.
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To solve low accuracy and efficiency problem of rapid prototype manufacturing in reverse engineering, a new algorithm was proposed to generate roughing and finishing tool paths on measured data directly by using Moving Least-Squares(MLS) method, and corresponding fitting error was analyzed. Roughing was performed in a slice-by-slice manner to remove material rapidly. An offset point cloud was firstly produced by the given machining allowance, and slicing data points were fitted by using MLS method to generate offset curve. Then whole region was partitioned into several sub-cut regions. Cutting path with a Zigzag way for roughing was obtained. Ball-end cutter was selected to guarantee machining precision, and offset point cloud was generated by offsetting point cloud a cutter radius and removing local interference points. Then, slicing data points were fitted to locate cutter location points. Data points were connected consequently to generate final cutting paths. Experimental results showed that the proposed method was efficient for roughing, and finishing could satisfy given accuracy while avoid local interference.
Article
Conventional algorithms for tool path generation from measured points did not use the region-by-region idea to generate adaptive tool paths since it is difficult to obtain geometric information of scattered points directly, which is necessary for adaptive tool path generation. This paper presents a new strategy for determining geometric information of physical parts measured and then three-axis numerically controlled (NC) adaptive (region-based) tool paiIis that overcome the inherent drawback (redundant tool paths) can be directly generated from measured points. A new algorithm for computing offsets of B-spline surfaces constructed using chosen point data as control points is also proposed in the paper.
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This article presents a method of generating iso-planar piecewise linear NC tool paths for three-axis surface machining using ball-end milling directly from discrete measured data points. Unlike the existing tool path generation methods for discrete points, both the machining error and the machined surface finish are explicitly considered and evaluated in the present work. The primary direction of the generated iso-planar tool paths is derived from the projected boundary of the discrete points. A projected cutter location net (CL-net) is then created, which groups the data points according to the intended machining error and surface finish requirements. The machining error of an individual data point is evaluated within its bounding CL-net cell from the adjacent tool swept surfaces of the ball-end mill. The positions of the CL-net nodes can thus be optimized and established sequentially by minimizing the machining error of each CL-net cell. Since the linear edges of adjacent CL-net cells are in general not perfectly aligned, weighted averages of the associated CL-net nodes are employed as the CL points for machining. As a final step, the redundant segments on the CL paths are trimmed to reduce machining time. The validity of the tool path generation method has been examined by using both simulated and experimentally measured data points.
Article
Due to the compute-intensiveness and the lack of robustness of the algorithms for reconstruction of meshes and spline surfaces from point clouds, there is a need for further research in the topic of direct tool-path planning based on point clouds. In this paper, a novel approach for planning iso-parametric tool-path from a point cloud is presented. Since such planning falls into the iso-parametric category, it intrinsically depends on the parameterization of point clouds. Accordingly, a point-based conformal map is employed to build the parameterization. Based on it, formulas of computing path parameters are derived, which are much simpler than the conventional ones. By regularizing parameter domain and on the basis of the previous formulas, boundary conformed tool-path can be generated with forward and side step calculated against specified chord deviation and scallop height, respectively. Experimental results are given to illustrate the effectiveness of the proposed methods.
Article
This paper presents a new approach for the generation of NC tool paths from random scanned data. Instead of using smooth or triangulated surfaces reconstructed from raw data, which is usually a time-consuming reverse engineering approach, the point-based surfel models computed by a GPU (graphics processing unit) are used to generate NC tool paths. The tool-path generation is highly efficient and still maintains the advantage of having accurate and smooth machining result. The word “surfel” itself is the combination of the two words “surface” and “element”. It is originally applied to the rendering of scanned data. In this paper, the point-based model is created using an elliptical Gaussian re-sampling filter that is based on a signal re-sampling algorithm. Since the input scanned data is of discrete and random nature, the warping process is utilized to transform the input data into a continuous surface and then re-sample the continuous surface by using GPU. Because the re-sampled data can accurately represent the original surface, tool paths can be generated based on the point data set. For cutting tools with various sizes, adaptive re-sampling schemes are employed to generate sufficient sampled points for the generation of accurate and smooth tool-paths.
Article
This article presents a method of generating iso-planar piecewise linear NC tool paths for three-axis surface machining using ball-end milling directly from discrete measured data points. Unlike the existing tool path generation methods for discrete points, both the machining error and the machined surface finish are explicitly considered and evaluated in the present work. The primary direction of the generated iso-planar tool paths is derived from the projected boundary of the discrete points. A projected cutter location net (CL-net) is then created, which groups the data points according to the intended machining error and surface finish requirements. The machining error of an individual data point is evaluated within its bounding CL-net cell from the adjacent tool swept surfaces of the ball-end mill. The positions of the CL-net nodes can thus be optimized and established sequentially by minimizing the machining error of each CL-net cell. Since the linear edges of adjacent CL-net cells are in general not perfectly aligned, weighted averages of the associated CL-net nodes are employed as the CL points for machining. As a final step, the redundant segments on the CL paths are trimmed to reduce machining time. The validity of the tool path generation method has been examined by using both simulated and experimentally measured data points.
Article
In reverse engineering, geometrical information of a product is obtained directly from a physical shape by a digitizing device. To fabricate the product, manufacturing information (usually tool-path) must be generated from a CAD model. The data digitized must be processed and in most cases, a surface model is constructed from them using some of the surface fitting technologies. However, these technologies are usually complicated and the process for constructing a surface patch from a massive digitizing data is time-consuming. To simplify the process for getting tool-path information, a simple algorithm is proposed in this paper. The algorithm is used to generate a 5-axis machining tool-path. Instead of implementing any complicated surface fitting techniques, a direct method is proposed for constructing three-dimensional (3D) triangular mesh from the digitizing data with the mesh points considered as the tool contact locations. Depending on the locations of the points digitized, a decimation procedure is applied such that some of the digitizing data will be filtered out. Then, the tool axis orientations which must be determined in 5-axis tool-path are calculated and the tool center locations are determined accordingly. A 3D biarc fitting technique is applied for all the tool center locations so that a complete 5-axis tool-path is obtained.
Article
Presented in the paper is a procedure through which 3-axis NC tool-paths (for roughing and finishing) can be directly generated from measured data (a set of point sequence curves). The rough machining is performed by machining volumes of material in a slice-by-slice manner. To generate the roughing tool-path, it is essential to extract the machining regions (contour curves and their inclusion relationships) from each slice. For the machining region extraction, we employ the boundary extraction algorithm suggested by Park and Choi (Comput.-Aided Des. 33 (2001) 571). By making use of the boundary extraction algorithm, it is possible to extract the machining regions with O(n) time complexity, where n is the number of runs. The finishing tool-path can be obtained by defining a series of curves on the CL (cutter location) surface. However, calculating the CL-surface of the measured data involves time-consuming computations, such as swept volume modeling of an inverse tool and Boolean operations between polygonal volumes. To avoid these computational difficulties, we develop an algorithm to calculate the finishing tool-path based on well-known 2D geometric algorithms, such as 2D curve offsetting and polygonal chain intersection algorithms.