A Method for Slicing CAD Models in Binary STL Format IATS-libre

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6th

International Advanced Technologies Symposium (IATS11), 16-18 May 2011, Elaz, Turkey

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A Method for Slicing CAD Models in Binary

STL Format

AbstractAdditive manufacturing (AM) is a technique that

fabricates parts layer by layer. As a result of this capability it

offers numerous advantages over conventional manufacturing.

This study concentrates on the process planning stage of the AM

and presents a STL slicing algorithm with the ability of G-Codegeneration.. This work is part of a wider range effort

concentrated on the development of an open-source AM system

therefore a special emphasis is given that all the software

packages used in this study are freely available open source or

freeware applications. The results and the capability of the code

are tested by simulating several complex 3D geometries on a CNC

milling simulator software using the generated G-Codes.

Keywordsdirect slicing, additive manufacturing, rapid

prototyping, STL format.

I. INTRODUCTION

dditive manufacturing (AM) is defined by a range of

technologies in which solid objects are built, directlyfrom 3D CAD models, by adding material in thin layers.

Physical parts which are technically impossible to produce

with conventional manufacturing methods are produced in

hours instead of days and at a relatively low cost. AM is

commonly used for producing prototypes of consumer

products, patterns for molds, and medical implants.

Research on the AM technology, which is also called as

Rapid Prototyping (RP), Layered Manufacturing (LM), and

Solid Freeform Fabrication (SFF), has been carried out in

various universities and companies for over 20 years. A small

list of some known commercial AM technologies includes:

Stereolithography (SLA) by 3D Systems, Selective LaserSintering (SLS) by DTM Corp., Fused Deposition Modeling

(FDM) by Stratasys Corp., Solid Ground Curing (SGC) by

Cubital and Laminated Object Manufacturing (LOM) by

Helisys. In addition to known commercial solutions, quite a

few AM processes are under development at various

universities such as University of Texas, University of

Michigan, University of Dayton, MIT, Stanford and Carnegie

Melon University [1]. The focus of the research is not only on

production methods but also on data exchange standard and

process planning.

The STL (STereoLithography) file format is considered to

be the de-facto data exchange standard for AM processes.

Most, if not all, of the major 3D CAD software packages

provide tools for STL conversion. The conversion is the

execution of a surface triangulation algorithm which is used

frequently in finite element analysis since 1970s. Shortcomings

of the STL format in terms of processing time and precision

set a barrier for demanding engineering projects [1-4]. While

some researchers suggest improvements to the STL, othersadapt existing CAD formats to AM or propose new formats.

Jacob et al. [4] reduce the file size of current STL format by

eliminating the repeating vertices data. Zhang et al. [5] use

models in IGES format in their welding-based AM system. In

[6], a new format PLY (Polygon File Format) is described. In

applications where high quality surfaces and dimensional

tolerances are less important, the STL format is well

researched and is appropriate for professional and non-

professional users of the area.

Process planning includes the steps for slicing the partstriangulated surfaces, tool path generation for each layer and

conversion of the tool path data to a suitable CNC data (i.e G-codes). The latter two steps are well established and are almost

identical to CNC milling. Different part slicing algorithms for

various AM processes exist in literature. Adaptive slicing [7]

is one of the approaches to resolve the inevitable staircase

effect by using variable layer thickness. The algorithm

proposed by Asiabanpour and Khoshnevis [8] saves each layer

data on a separate file in order to ease path generation process

and free computer memory. In [9], a slicing method suitable

for Color Rapid Prototyping (CRP) is presented. There is

presently no industrial or formal standard for slice data. As a

result the developer or the manufacturer is free to decide on or

to develop its own slice data to create the required AM

machine code. Some proposals made in this area are listed

below.

Common Layer Interface (CLI) represents each layer by

its thickness and a set of contours. These contours define

the boundaries of the solid material;

Layer Exchange ASCII Format (LEAF) provides each

contour as a non-self-intersecting polygon described in

terms of 2D primitives, the polyline and the circular arc;

SLC Formats represents several slice formats that use a

polyline approximation to represent the contours of a

slice.

A Method for Slicing CAD Models

in Binary STL Format

O. Topu1, Y. Tacolu2and H. . nver3

1TOBB University of Economics and Technology, Ankara, Turkey, [email protected] University of Economics and Technology, Ankara, Turkey, [email protected] University of Economics and Technology, Ankara, Turkey, [email protected]

A


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The AM process is mainly composed of three stages. First

stage includes 3D CAD modelling and STL conversion.

Nowadays this stage can be performed by using the freely

available 3D modeling software such as SketchUp 3D,

CoCreate Modeling Personal Edition, PowerShape-e and etc.

Second stage is the aforementioned process planning and the

final stage is the production of the physical part, which

depends entirely on the AM machine.

This study concentrates on the second stage of the AM

process and presents a STL slicing algorithm with the ability

of G-Code generation. Special emphasis is given that all the

software packages used in this study are freely available open

source or freeware applications. This work is part of a wider

range effort concentrated on the development of an open-

source AM system.

II. SLICE ALGORITHM

Figure 1: (a) a tessellated cube with twelve facets (b) a sliced cube

Fig.1(a) shows triangulated STL representation of the

surfaces of a simple cube shape and Fig.1(b) shows the sliced

cube. The algorithm is mainly developed to obtain the contourdata of the desired slicing level. As a result it does not have the

capacity to slice some facets which are positioned between two

slicing planes where no intersections occur. This problem can

be solved easily by reducing the gap between two adjacent

slices. The gap between two adjacent slices defines the layer

thickness which is also a variable inside the code. Also, the

software code is developed based on the assumption that the

STL representation of the geometry is error-free and is

normally assigned in the z-direction. Intentionally, the

developed code has divided into separate sections which carry

on the calculations based on the results of the previous section.

This approach has simplified the debugging process and made

the code more flexible when needed.A. Intersection Point Detection

Figure 2: Possible intersection cases.

The first section of the slicing algorithm finds intersection

points between equally set apart slicing planes and the

imported STL data of the solid body. Given the oriented

model, part slicing is a purely geometrical process. Figure 2

exemplifies possible relations between the slicing plane and a

facet of the model.

From this point on the mentioned facet will be labeled as F,

its vertices as V1, 2, 3(x1, 2, 3, y1, 2, 3, z1, 2, 3) and its normal vector

as N (xn, yn, zn). Normal vectors are required for graphical

visualization of the solid body on a computer screen hence

they are omitted in the slicing algorithm.

According to slicing planes z-axis value, z, there are fivekinds of different positional relationships between the slicing

plane and the corresponding facet, as shown in Fig.2 and listed

below:

1) z1=z & z2=z & z3=z.

2) z1=z & z2=z & (z3z).

3) z1=z & ((z2z) || (z2>z & z3z)) || ((z1>z) & ((z2z) || (z2


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common form of the well-known line equation (1), where the

slope is m and the two variables are x and y.

bmxy (1)

Also in CASE III, z values of the corresponding points are

both stored as 1. This coding enables the algorithm toidentify the obtained line data in further parts of the code.

In CASE IV, none of the Fs vertices touch the slicing planebut one of the vertices is on the other side of the plane when

observed from x- or y-axis. As expected, this case creates two

intersection points. Obtained line data is also labeled with

1.In CASE V, F touches the slicing plane at a single point

which is redundant information for the rest of the code.

The outputs of the intersection point detection algorithm are

all the points that are located on the slicing plane with the

appointed classification reference values.

B. Line Creation

Fig.4 shows the algorithm that is designed to create lines ofthe slice data with mentioned z values. Line creation algorithm

is similar to the intersection detection. For simplicity and

future improvement possibilities, it is kept apart as another

process.

Figure 4: Line generation algorithm.

The outputs of the line creation algorithm are lines that are

obtained from the outputs of the aforementioned intersection

point detection algorithm with the appointed classification

reference value. Tab.1 show the column labels of the outputdata arrays where the number of points and the number of lines

represent the row count of the array. The z values are

unchanged and the two associated points are grouped to create

a line.

Table 1: Output data of intersection point detection and line creation

algorithms.

Output Data Column labels of the array

Point Array x, y, zref

Line Array x1, y1, x2, y2, zref

C. Repeating Lines

Fig.5 represents the overlapping lines which happen when

two facets share an edge at the slicing plane.

Figure 5: Repeating line cases.

As an example, top of a cube can have 10 lines after line

creation algorithm. However, only a polygon with 4 lines is

enough to draw the boundary of the cube. In order to define

interior and exterior of the contour the repeating lines must be

removed or merged into a single line. At this point, previously

stored z values 2, 1 and the reference values playimportant role. Comparison between these values and the z

values of the overlapping lines zLine1and zLine2are listed below:1) zLine1=2 & zLine2=2.2)

(zLine1=2 & zLine22) || (zLine12 & zLine2=2).3) ((zLine1< z & zLine2> z) || (zLine1> z & zLine2< z)).

4) ((zLine1z)).

In the first case (Fig.5 CASE A), neither line represent any

boundary. Therefore these two lines are removed from the data

that is going to be used to obtain the edge contour at that

slicing plane.

In the second case (Fig.5 CASE B), both lines reside in the

same edge and one of them is removed from the data. As a

fact, which line is removed does not matter; because the

obtained contour data does not need any reference

information.

In the third case (Fig.5 CASE C), both lines share the same

edge that is actually a boundary for the solid body.

Consequently one of the lines is removed.

In the fourth case (Fig.5 CASE D), the edge does not

represent any boundary of the solid body when the slicing

plane is considered. In other words, this data do not create a

closed area which is going to be built in the AM process at

further points. As a result both lines are removed from the

contour data.

The outputs of the repeating lines algorithm are the lines

that represent the boundary of the solid body on the slicing

plane.

D. Line Grouping

Line grouping is rearranging of the vertices so that they

form a closed loop. This closed loop defines the hatch path

boundary. Hatch path generation is necessary when additive or

subtractive building processes are used to shorten production

time and improve surface quality. In this study, line grouping

is omitted because the aim of this study is to understand slicing

procedure and use this knowledge as a base for future AM

process developments.


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E. G-Code Generation

This section of the algorithm uses the standard milling G-

Code. Only a few machine codes are sufficient to create the

required slice as a layer of the whole artifact. The algorithm

traces the whole slice data along the x-axis of the slicing plane

for every y-axis value and then marks the required locations.

In other words, it detects the locations of start and end points

of the building process. If the STL file is error free, there

exists an even number of marking points. The schematic

illustration of G-Code generation obtained from a hollow cube

solid is given in Fig.6 The dark, thick lines symbolize the solid

and the light, thin lines symbolize the empty space.

Figure 6: (a) Schematic illustration of G-Code generation and (b)

resultant code of the algorithm.

III. CASE STUDIES

Examined geometries, which are specially chosen for the

purpose of this study, are shown in Fig.7. Single layers of

these geometries are tested on CNCSimulator [10], a freeware

CNC milling simulation software, by using the G-codes

generated with the algorithm described at the previous section.

Hollow cube and Keplers rhombic dodecahedron solid bodiesprovide all the cases mentioned in the intersection point

detection algorithm. For this reason these models are

frequently used to detect bugs in the coding phase.

Figure 7: Studied geometries to test the competence of the

algorithm.

Fig.8 and Fig.9 depict the simulation results of the two

studied geometries. As it can be seen, slices of relatively

complex 3D parts have been simulated using the developed

slicing and G-Code generation algorithms. The resolution

difference between the figures is due to difference in the step

size of the G-Code. The step size is determined from the

dimensions of the workpiece. Fig.8 shows one of the slices of

the whole part obtained from a 100mm x 100mm x 1mm

dimensioned rectangular solid. Fig.9 shows one of the slices

produced from a 1m x 1m x 1mm in size solid rectangular

workpiece.

Figure 8: CNC milling simulation result of logo 1.

Figure 9: CNC milling simulation result of logo 2.

IV. CONCLUSION

In this study a new STL slicing and G-Code generation

algorithm was explained. This software algorithm shapes the

foundation for future studies and generates slice data of any

given 3D model. Performance of the algorithm is evaluated by

simulating several complex 3D geometries on a CNC milling

simulator using the generated G-Codes. There is currently a

limitation on the STL file size but this limitation can be

handled by a modifying the code to study with one facet data

at a time. Moreover, considering that the operation of integers

is faster than that of floating point numbers, the floating pointcoordinates of the facets in a model may be transformed to 32

bits integers to speed up the process.

ACKNOWLEDGMENT

The authors appreciate . Ethem Bacs guidance forNetBeans IDE and Javasmemory heap problem.


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