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How to Make a 3D PrintMathematically speaking, the 3D print is constructed from a 1dimensional path. This article will describe how to find that path...David Austin
IntroductionWe frequently hear that we are in the midst of a 3D printing revolution. Indeed, a recent story on the PBS Newshour compellingly demonstrates how 3D printing is being used in a wide range of areas from medicine to the arts. Though some of the claims may sound overblown, my experience as a mentor to a team of high school students preparing for a robotics competition shows how simple it is to 3D print custom parts and prototype ideas quickly and efficiently. After using the printer for a while, I began to wonder how the process works. Each print is created layer by layer from a spool of plastic filament that is slightly melted and extruded from a nozzle moving along a planar path. Mathematically speaking, the 3D print is constructed from a 1dimensional path. This article will describe how to find that path. To be more specific, most 3D prints begin as a file written in the STL (stereolithography) format. Most STL files are created by 3D design software though the format is simple enough for you to write them yourself. For instance, here is a piece of an STL file:
In this format, the boundary of the solid is described as a list of triangles, each of which is specified by stating its three vertices and a normal vector. This file is converted into a set of instructions in Gcode, a language widely used in numerical control machines, and these instructions are sent to the printer. Here is a bit of the Gcode created from the STL file.
The This article will outline how the STL file is converted into Gcode instructions by the RepRap Project, an open source 3D printing community project. RepRap claims to be "humanity's first generalpurpose selfreplicating manufacturing machine." This claim may be a bit strong, however: the printer can print many, but not all, of its own parts, and it can't assemble them. Nevertheless, the source code is freely available and easy to read, which is why it's fun to follow along.
The mechanics of 3D printingBefore we begin our description of the STL to Gcode conversion process, let's look at the physical machine we will be controlling. The pictures that follow are of a MakerBot Replicator 2.
With this outline under our belt, let's start digging into the algorithm that creates Gcode. Slicing the solid into polygonsRemember that our STL file contains a list of triangles that form the boundary of the solid we are printing. It is important to note that there could be a huge number of triangles since our design software will approximate a curved surface with many triangular patches.
Now that we have determined the set of polygonal curves that arise as the intersection of the current slicing plane with the solid, we arrive at an interesting problem. Suppose one layer of our solid looks like this.
It may seem that we could simply tell the extruder nozzle to trace out these polygonal curves and then fill in the interior. However, the thickness of the filament would cause the plastic to spill over the edge of the filled region so we would not be accurately rendering the slice. Instead, we need to move the path of the nozzle into the region by half the width of the filament.
As the figure shows, this can be a tricky business. Edges of the polygonal boundary may disappear, others may be broken into smaller pieces, and the topological characteristics of the region may change. Solving this problem requires some work and some interesting ideas. We will begin by describing the filled region using Constructive Solid Geometry. The CSG representation of a polygonConstructive Solid Geometry, or CSG, gives us a convenient way to represent a set of points and work with it inside a computer program. In essence, CSG considers sets as being constructed from simpler sets used as building blocks and put together with a few simple rules. In our application, the building blocks are halfplanes, and the simple rules for putting them together are the familiar settheoretic operations of complement, intersection, and union. An oriented line defines a preferred halfplane $H$ to the left of the line when moving in the direction implied by the orientation.
It will often be useful for us to think of $H$ as defining a boolean function on the plane: $H(p) = \hbox{True}$ if and only if $p \in H$. The operations of intersection, union, and complement produce these results.
Notice that the difference of two sets may be expressed in terms of these operations: $A \setminus B = A \cap \overline{B}$. Observe that convex polygonal regions have a particularly simple expression. If we orient the edges of a convex polygon $P$ so that we travese the polygon in the counterclockwise direction, then the polygon is given by the intersection of the halfplanes defined by the edges.
In fact, it is straightforward to describe any polygonal region in terms of convex polygonal regions. To this end, remember that the convex hull of a set of points is the smallest convex set containing that set of points. For instance, is we start with this set of points:
we find the convex hull:
As we'll see momentarily, there is a straightforward algorithm for finding the convex hull of a set of points. Now there are many possible CSG representations, and several algorithms for finding one. Since convex sets have simple CSG representations, however, we choose the following method. Suppose we would like to find a CSG representation of this region:
We first consider the outer polygon $P$ and find its convex hull $A$.
The fact that the original polygon $P$ is not convex is detected by traversing the convex hull and noting that we skip some of the points of $P$, which themselves form a new polygonal region.
The original polygonal region $P$ is the difference in its convex hull $A$ and this new polygonal region, whose convex hull we call $B$.
Notice again that the new polygonal region is the difference in its convex hull $B$ and the regions $C_1$ and $C_2$.
Since $C_1$ and $C_2$ are themselves convex, we arrive at a CSG representation of $P$ in terms of convex sets: \[ P = A \setminus (B \setminus (C_1 \cup C_2)).\] It is convenient to express this represenation as a binary tree:
In this representation, each of the leaves of the tree are convex sets, which are described by the intersection of the halfplanes defined by the edges. We therefore replace the leaves of this tree with binary trees representing the intersection of these halfplanes. The result is a new binary tree whose leaves are halfplanes. This binary tree representation can be naturally constructed in our code. Furthermore, we may view this expression as a booleanvalued function on points in the plane, as we mentioned earlier. For instance, if $p$ is a point in the plane, we may now determine whether $p$ is inside $P$. Beginning with the root, we evaluate the two binary subtrees and join them with the appropriate logical operation.
Among other things, this makes it easy to determine, by evaluating $P$'s booleanvalued function on other polygonal curves found in this layer, that there is a hole $H$ that needs to be removed.
This leads to the full tree
The QuickHull AlgorithmWe now have a way to obtain a CSG represention of a layer's filled region in terms of convex sets. All that remains is an algorithm to determine the convex hull of a set of points. The algorithm used by RepRap is called QuickHull.
The boolean gridUsing our CSG representation of the filled region, we are now in position to determine the path taken by the extruder nozzle. We need one more ingredient, which we'll call a boolean grid. Since the nozzle of our printer is positioned with stepper motors, there are only a discrete number of positions that it can visit. We will use this fact by placing a grid of points, representing these positions or pixels, on the plane.
Considering the CSG representation of our filled region as a booleanvalued function $F$ on the plane, we may determine which of the pixels are inside our region; namely, $p$ is inside the region if $F(p)$ is True.
Of course, we could determine these pixels by checking the value of the CSG expression at each pixel. However, a more efficient algorithm uses another quadtree and this simple observation: Given a rectangle $R$ and a halfplane $H$, all the points in $R$ are in $H$ if and only if the four vertices of $R$ are.
Remember the shape of our CSG tree and recall that each of the nodes $A$, $B$, $C_1$, $C_2$, and $H$ are themselves binary subtrees representing the intersection of the halfplanes defining the convex sets.
We begin by dividing our region into four rectangles and studying each in its turn.
In each of the four rectangles, we may "prune" the CSG tree by evaluating each of the four vertices of the rectangle on the leaves of the CSG tree. Consider, for instance, the lower left rectangle and the lower edge of the hole $H$. Evaluating each of the four vertices of this rectangle by the halfplane defined by the lower edge of the hole $H$ gives False. In other words, there is no point in the lower left rectangle that intersects $H$. In fact, the same argument shows that no point in this rectangle intersects $C_1$. This means that, when looking in the lower left rectangle, we need only consider the smaller tree:
Even the subtrees defined by $A$, $B$, and $C$ may be pruned since the four vertices of the rectangle evaluate to True for many of the halfplanes defined by the edges of these convex sets. We now descend this into rectangle by subdividing it into four rectangles, and consider the upper right rectangle that is created.
Remember that we only need to evaluate this rectangle against some of the halfplanes in $A$, $B$, and $C_2$. When we do this, we see that the rectangle is contained in $B\setminus C_2$, which means that it is not inside our polygonal region. We may therefore set all the pixels inside to False. As indicated by this example, pruning the CSG tree as we move down the quadtree allows us to efficiently evaluate the boolean grid. We have now determined that the orange pixels are the ones inside the filled region.
Shaving the boolean grid to find the nozzle pathNow that we have determined the pixels inside the fill region, we may determine which pixels need to be shaved off to produce the path we want the nozzle to follow. We will denote half the width of the nozzle by $r$ so we would like to move each of the edges into the region by a distance $r$. For each edge of our region, we create a rectangle of width $r$ and set all the pixels inside that rectangle to False. Shown below is the rectangle for one of the edges.
In fact, we may find the pixels inside the rectangle, as before, using a quadtree that begins with the bounding box of the rectangle. Around each vertex, we also shave off a circle of radius $r$. This results in a new boolean grid.
From this point, we identify the nozzle path by finding the pixels on the boundary that are not surrounded by pixels in the region.
The nozzle path is determined by walking around this boundary. Rather than ask the nozzle to move from boundary pixel to adjacent boundary pixel, an algorithm is applied to determine when a set of adjacent pixels are sufficiently close to lying on a straight line. This results in the final nozzle path.
CrosshatchingAt last, we have found the nozzle path that outlines the boundary. Since we are creating a solid, we also need to determine how to fill it in. In many 3D printers, we are able to specify how much of the interior, a percentage perhaps, we want filled. The printer uses this percentage to create a crosshatch pattern.
Given our CSG representation of the region, this is fairly simple. Begin by considering all the possible grid lines.
For each grid line, we determine the intersection points with the boundary path and order the points along the line. For each segment joining two adjacent intersection points, we then use the CSG representation of the region to determine whether the midpoint of the segment is in the region and, hence, whether the segment should be traced by the printer. SummaryIn describing this process, I have made a number of simplifications, but this outline gives the essential ingredients. There are also, at several steps in the process, different choices that one could make. The CSG representation of the fill region is not unique, and, in fact, there are representations that may be obtained and used more efficiently. I have described this representation since it is the one used by RepRap and it is relatively simple to explain. An alternative representation, in which each edge of the polygon is used exactly once, is given in the references (Dobkin, et al). The problem of finding the nozzle path from the polygonal curves may also be solved in other ways. The method using a boolean grid exploits the fact that our 3D printer has a specific resolution. Another solution, which has a more geometric flavor, is also given in the references. References

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