3D Objects, Engineering, Optimizing 3D Prints, Sustainability

Optimizing 3D Prints- Results: Tomography and Morphological Variations (Part 1)

Results: Tomography and Morphological Variations

The X-ray computed tomography shows the differences in the external shell of the prints as well as the internal structure of the infill. Each layer of PLA can be easily observed in the images. For simplicity, the most prominent image from among the hundreds of images in the dataset are represented in the Fig. 5-7. The number on their top right corner is the corresponding image taken from the captured dataset. The blue objects were not scanned due to the insufficiency of time and lengthy scanning process. Fig. 5-7 show one of the hundreds of images captured during the CT scan. The difference in the background colors is because of the adjustments made to get a good contrast wherever necessary.

Fig. 5 X-ray CT scanned images of the outer shell of all objects.

 

Fig. 6 X-ray CT scanned images of the vertical cross section of all objects

 

Fig. 7 X-ray CT scanned images of the horizontal cross section of all objects

 

There are very few differences in the morphological structures of the cylinders of either color with the same infill level. There are, however, variation in the way the infill is printed inside the shell of the objects. It is to be noted that in Fig. 6 and Fig. 7, the cross-sectional images with a darker background have a different contrast level than that of the images with lighter background. This happened during image adjustment using the software NRecon, which is used to reconstruct the shadow projections. It does not affect the analysis.

When performing the scans, it might not be possible to capture the entire object as the field of view of the receiver is limited (less than 30 mm). Hence only the top portion of the cone was captured. In the case of the cylinders, again, the top was captured, but since the diameter was around 30mm, the detector could only receive a little over 4/5th of it. So, only a part of the wall can be seen. Again, this does not affect the measurement, as the objects are symmetric about the vertical planes.

 

References

References can be found in the Introduction section.

3D Objects, Engineering

X-Ray Tomography (Part D)

When all the images were finally scanned (seriously, I may have used the CT scanner more than Ph. D. candidates in a few weeks), there is only one process remaining: Analysis (and visualization, and interpretation, and inference, and the write up, and the dataset organization and many more).

The scanned images can be easily saved in popular formats such as png and tiff. This makes them easy to view in commonly available image viewing software which, we all know is Microsoft’s Photo viewer, because Google decided to discontinue Picassa (which is a shame, in my opinion)…

Skyscan comes with its own analysis software called CTAn, which can not only be used to analyze individual images, but also measure tiny flaws if found! Perhaps the most amazing feature is to analyze multiple images at the same time.

When the region of interest is set for an upper limit and lower limit of an image sequence. Threshold can be set for binary images for each image or the entire data sequence to see the histograms. With this, density can be found (i.e. the density of the poly lactic acid that is used to fill in the specimen in this particular case). In the end it is possible to find the mean total value of voxels (simply put, 3 dimensional pixels) and save the calculations if necessary, and it is, because we’re analyzing. Then, use them to calibrate the attenuation and compare results. The same process is repeated for each individual scanned specimen. Quite mind-numbing, but necessary for what I was doing. Below is an example of a high infill colored cone (20%, pink).

A Marked Region of Interest and Histogram of the Dataset of a Colored Cone

Another important feature of CTAn is to show Density Profiles of each slice of image. but the most underrated and less frequently used feature is to perform dimensional measurements, which was the primary focus of the Optimization of 3D Prints project. Dimensions such as layer thickness, empty space areas inside the object, position of each layer, alignment of layers, angle between two subsequent layers, thickness of the shell etc. could be calculated, which was a tedious task to perform (the things we do to seek the truth, am I right?). With this it was possible to do additional statistical analyses.

Example of Dimensional Measurement of a Hollow Colored Cone showing Angle between 2 Layers

Then there is another software called CTVox, which is used to construct a 3 dimensional view (also called volume rendering in this case) of the internal and external morphological features of each specimen. I may upload videos of them in the future, but right now, there is only a picture as each of them can be a whopping 10 giga bytes (and they look beautiful)! Below is an example image of a volume render of a cylinder.

Volume Rendering of a High Infill Cone

It is also possible to create moving Heat Maps in CTAn, if you know what you’re doing, like I showed in this particular post. Heat Maps are very cool (and so are oxymorons)!

With this, I conclude this (slightly comical) mini-series of showing how X-ray Tomography can be done, and how it was used for my project. Sorry, but there is no party (I meant Part-E).

Starting from the next time, we’ll return to Optimization of 3D Prints and finally see how the project ended.

3D Objects, Engineering

X-Ray Tomography (Part C)

There is a good reason why this article is posted after more than one month. This is because I wanted to get a feeling for how long the scan takes in reality and re-live it… (Or, I may have lied and I was busy with something; we’ll likely never find out.)

Now that the scan is over, the images had to be reconstructed to get a 3D map of the scanned specimen. It uses an algorithm that I can’t seem to name, because I didn’t write it down anywhere. Fortunately, I know exactly what it does. It creates slices of images which show the density within the specimen at specific heights (i.e., find out how much empty space there is and how much filled space there is in each sliced layer the object).

The software NRecon was used to reconstruct the captured images into full-fledged 3D images of high quality. A correction must be made for each image to compensate for any deviations caused by the temperature during scanning, while the images were being captured. There are several options available for this procedure. Fortunately, since the scanner itself was new, the corrections were pretty minor.

Density of a Certain Vertical Slice of a Transparent Cylinder

Next is to compensate for beam hardening, if any. This is done to keep the densities flat. After this, would be ring artifact corrections, which is done to rectify the formation of rings in the reconstructed images due to miscalibration of the sensor—we’re all humans, so these things can happen during initial setup. Rings are bad. The images with them can be rectified, however. Below is an example of a ring artifact, which, again, is undesirable. This is especially true if your image begins to look like a vinyl record…

Ring Artifacts Formation in the Horizontal Slice of a Cone

There is a tool for reducing noise in the image and smoothening them. The images can then finally be saved in various formats. Saved images can then be visualized and analyzed using other software. I have my images in BMP and TIFF formats.

Fortunately, batch processing of reconstruction is an option and large quantities of obtained images can be corrected and reconstructed with the click of a button, once the settings are ready. Imagine sitting and having to reconstruct each individual image, then save them, and then analyze them… it would take months, especially if the resolution is 4K!

The reconstruction process was done for 4 types of infill levels for colored cones, and both transparent and colored cylinders (a grand total of 12 types of data sets with 3 sub types within them, each) in my project. That genuinely took a lot of time.

With this, we end another part on this extremely interesting process of reconstruction. It looks short when you read it, but it is ridiculously convoluted, especially if you’re doing it for the first time. Next time we will talk about visualizing the images in 2D and 3D, and maybe a bit on how to analyze them.

3D Objects, Engineering

X-Ray Tomography (Part B)

Now to start the scan.

Nope. Not yet. We have some housekeeping to do, before that happens.

The base of each specimen was flat enough that no additional materials (like wax) was needed to hold it in place. The paraffin film did a good job of keeping these relatively large (when compared to the X-Rays, of course) objects in one spot. Good. Now the specimen is in its place and its stage is mounted inside the scanning chamber. Close the door—safety first, remember? Yes, yes you do—and prepare for the beam to energize.

One of the advantages of living in today’s world is that you can make a software control your hardware without having to manually adjust things. Apparently, when they wanted to do these experiments, in the olden days, they used to manually adjust the stages for each performance (no, that was a lie). The SkyScan software was used to adjust position of the specimen—vertical, horizontal, radial, you name it.

It was necessary to adjust the voltage and current, so that the power of the X-Rays emitted but the emitter gun would always be around 10 watts and never exceeded it. This was done to adjust the contrast of the images. The voltage and current were 44 kV and 222 μA for this experiment. (Psssttt… multiply the two to get the power).

Next was an important step called Flat Field Correction, which I’m fondly going to call FFC and never use it again. This step is used to have a uniform brightness in the background and calibrate the sensor on the other side. This was when the resolution, pixel size, etc. had to be chosen.

And finally, it was time to scan. The step angle of the stage’s rotation was set to an appropriate amount to not waste the time. Smaller the angle, longer the scanning time. I’ve seen some scans happen for days!

The camera sensor was set to capture multiple images during each rotation step and average them out to reduce errors and smoothen the final image by a process called Frame Averaging. There was also Random Movement correction to take care of any dead pixels, because cameras are dainty and don’t age well.

As far as I can remember, there was also an option to turn the X-Ray off or leave it on after the scan ends—off should technically have been the only option… because we’re talking about X-Rays here.

Alright! Now, the scan has begun, and below is an image of the Scanner preparing to do its thing.

Here are some of the details I collected from the log file, because obviously, I can’t remember everything that happened in August 2017 at them moment (Yes, that was when the scan was done, and the actual project had started months before that):

Source Type = Hamamatsu 100/250
Camera = SHT 11Mp camera
Camera Pixel Size (μm) =    9.00

Source Voltage (kV) = 44
Source Current (μA) = 222

Frame Averaging = ON (6)
Random Movement = ON (8)
Vertical Object Position
(mm) =33.693
Exposure (ms) =   238
Rotation Step (deg) =0.300

These are only some of the setting. There were more; I just don’t want to make these posts extremely technical. More stuff on reconstruction, visualizations, and analyses another time.

3D Objects, Engineering

X-Ray Tomography (Part A)

X-Ray Computed Tomography is a technique constantly used in medical imaging. You might have heard about CT Scans… Sounds very Sciencey, Medical, and Technical. Because, it is. The CT in CT Scans is short for Computed Tomography. CT Scans can also have non-medical application. For example, seeing what is inside of non-living things, like 3D printed objects—my topic of interest in this instance.

Why am I explaining something I had previously mentioned in a post (kind of)?

Because this is a filler post!

No, it’s not a filler, but I wanted to explain how exactly I did the Tomographic scans of the 3 D printed objects for the Optimization of 3D Prints project, before completing its story through more posts.

The CT Scanner used during the whole process of analyzing the 3D objects was Skyscan 1172 Micro-CT Scanner. Before beginning a scan, safety precautions must be taken, everything should be kept clean, the scanner must be hooked to a computer with powerful graphics card, relevant software must be installed, and this is very important—the power must be turned On. Of course, the machine is designed with all the safety measures taken into consideration. In fact, the X-ray source won’t work if the compartment (look at the image below) is open, even if it is told to start the operation by the software. But still, the most important thing to keep in mind is that the machine is a powerful source of X-Rays, so safety first!

Now we are ready to place the object of interest (which we usually call, a specimen) on one of the many pedestal-types (they are also called stages for some reason, as if the camera is taking the photos of some super model) for the specimen to be scanned, which in this case would be all the different types of printed objects of different infill. The specimen was covered in a paraffin sheet to keep it in place. Paraffin sheet is used because it is transparent to the X-Rays (i.e., the X-Rays ignore it, like a person ignores their ex). These initial settings are a bit convoluted, but they must be performed to capture good quality images without the formation of unnecessary rings in the final images (for now, take my word for it, I know what I’m saying when it come to this). The Skyscan1172 software helps in doing all of these initial operations such as adjusting the voltage and power levels, adjusting the pixel size of the images to be captured, the field of view, position of the object, and other relevant parameters can be adjusted with the software.

Inside the CT Scanner

I don’t want to make this post boring with even more technical details, so in a layman’s example, the setup can be seen (in the image above) for a cylinder inside the compartment of the CT scanner. Behind the cylinder is the camera/sensor, and on the left side (the open square box), is the X-Ray source. More on the technical aspects another day. (Because I want to try and explain some of the details about why this process is complicated and takes time, and the analysis of the data obtained from this takes even more time).

Once the images are captured, certain settings need to be adjusted and images must form the whole picture in the end for analysis: size of the image to be captured, position of the camera, etc. This and more can be done in a software meant to be used with the CT scanner called NRecon. The software shows a captured image. As an example, the image (see below), shows the frustum of a cone when observed by the sensor at a particular angle.

The turn-table-pedestal-stage-thing will rotate the specimen as the stationary sensor captures sectional images, while all along, the source showers the specimen with X-Ray beams. These images are reconstructed using NRecon, where the HSI levels, contrast and other adjustments need to be made before reconstruction of captured image for analysis. 1000 images each were captured for a variety of infill levels and objects of different shapes in my project (Honestly, this number is nothing. You should see the Biology researchers have a go at it for the real deal). The image below shows a snapshot of some of the settings chosen, which was kept constant for all the different objects.

A Snapshot of NRecon in Use

In Part B, I’ll get to the real stuff: the Process of Everything!


P.S.: You guessed it right, this post was supposed to come out a week ago, and it did! However, due to unforeseen circumstances, I couldn’t finish writing it. Unfortunately, the draft was scheduled to be published back then. Even what’s written in this article is incomplete, which is obvious from the Part A in the title. I need more time to finish Part B. Who knows, there might even be a Part C, Part D… Party! We’ll see… Woe is me…

 

3D Objects, Engineering, Optimizing 3D Prints, Sustainability

Optimizing 3D Prints: Results: Optimum Configurations for 3D Printing (Part 2)

Results: Optimum Configurations for 3D Printing

The summary of optimal settings obtained in the case of Experiment-1 and Experiment-2 can be found in Table 2 and Table 3 respectively. It shows the most ideal and least ideal configurations to use when it comes to choosing between the factors. It also shows which factors, or the factorial interactions contribute to the printed object in a statistically significant manner. This indicates the user to keep an eye on them.

Infill (Factor B) Most Ideal Configuration Least Ideal Configuration Statistically Significant Factors
Low High Height Base Area Height Base Area Height Base Area
Hollow 20% Natural

20%

None

Natural

20%

None

Natural

20%

Tapered

Natural

Hollow

Tapered

C No

Factors

Hollow 80% Natural

80%

None

Natural

80%

None

Pink

80%

Tapered

Natural

80%

Tapered

C B
Hollow Solid Natural

Solid

None

Pink

Solid

None

Pink

Solid

Tapered

Natural

Solid

Tapered

No

Factors

No

Factors

20% 80% Pink

80%

None

Pink

80%

Tapered

Pink

80%

Tapered

Natural

80%

Tapered

A, C

A*C

A*B*C

A

A*B, A*C

A*B*C

20% Solid Natural

Solid

None

Pink

20%

None

Pink

20%

Tapered

Natural

Solid

Tapered

A, C

B*C

B
80% Solid Natural

80%

None

Natural

80%

None

Pink

80%

Tapered

Pink

80%

Tapered

A, C B, C

A*C

Table 2 Summary of the results of the optimal configurations of Experiment-1

 

Infill (Factor B)

Most Ideal Configuration Least Ideal Configuration

Statistically Significant Factors

Low High Height Base Area Height Base Area Height Base Area
Hollow 20% Natural

Hollow

None

Natural

20%

None

Natural

Hollow

Tapered

Blue

20%

Tapered

C

A*C

B
Hollow 80% Natural

80%

None

Natural

80%

None

Natural

Hollow

Tapered

Natural

Hollow

None

C B, C

B*C

Hollow Solid Natural

Solid

None

Natural

Solid

None

Natural

Hollow

Tapered

Blue

Solid

Tapered

C

A*C

A

A*B, B*C

20% 80% Natural

80%

None

Natural

80%

None

Natural

20%

Tapered

Blue

20%

Tapered

C

A*C

A*B*C

C

A*B

20% Solid Natural

Solid

None

Natural

20%

None

Natural

20%

Tapered

Blue

Solid

Tapered

C

A*C

A, B, C
80% Solid Natural

80%

None

Natural

80%

None

Blue

80%

Tapered

Blue

Solid

Tapered

A, C

A*B, A*C

A*B*C

B, C

A*B

Table 3 Summary of the results of the optimal configurations of Experiment-2

 

When color pigments are added to natural PLA, some of its properties such as crystallinity is affected [25], leading to variation in the way the material prints. Hence, a similar experiment was performed with two different pigmentations of PLA. Factor A’s levels were changed to pink and blue. However, other factors and the settings were kept the same. The expected values also remained the same. Table 4 shows the optimal configurations for the Experiment-3.

 

Infill (Factor B)

Most Ideal Configuration Least Ideal Configuration

Statistically Significant Factors

Low High Height Base Area Height Base Area Height Base Area
Hollow 20% Blue

20%

None

Pink

20%

None

Blue

Hollow

Tapered

Blue

20%

Tapered

No Factors No

Factors

Hollow 80% Blue

80%

None

Pink

80%

Tapered

Pink

80%

Tapered

Blue

Hollow

Tapered

No Factors B
Hollow Solid Blue

Hollow

None

Pink

Solid

None

Blue

Solid

Tapered

Blue

Solid

Tapered

No Factors No

Factors

20% 80% Blue

80%

None

Pink

80%

Tapered

Pink

80%

Tapered

Blue

20%

Tapered

A, C

A* C

A, B, C

A* C

20% Solid Blue

Solid

None

Pink

20%

None

Pink

20%

Tapered

Pink

Solid

Tapered

A, C

A* C

A, B, C

 

80% Solid Blue

Solid

None

Pink

80%

Tapered

Pink

80%

Tapered

Blue

Solid

Tapered

A, B, C

A*C, B*C

A, B, C

A*C

A*B*C

Table 4 Summary of the results of the optimal configurations of Experiment-3

 

The data from Table 2-4 show that tapered objects should have a lower priority while 3D printing. The bigger the shape, the more accurate the overall geometry [20], hence the cones can clearly be seen having the least ideal configuration in all cases, because the size of each successive layer reduces since they taper. Also, objects printed using natural PLA are consistently seen in the most ideal configuration columns in Table 2-3, making it preferable when compared to its colored counterparts. Choosing the settings available in Tables 2-4 could prove beneficial to reduce filament wastage while printing using PLA.

 

References

References can be found in the Introduction section.

3D Objects, Engineering, Optimizing 3D Prints, Sustainability

Optimizing 3D Prints: Results: Optimum Configurations for 3D Printing (Part 1)

Results: Optimum Configurations for 3D Printing

When the factorial analysis was performed, each of the three experiments had six sub-experiments for every combination of the infill level. Each of these sub-experiments produced graphs and charts for further analyses to obtain the sets of optimal configurations. Fig. 3 shows one example with the pareto chart and cube plot in the case of the second experiment with an infill setting of 20% and 80%. Fig. 4 shows the main effect and interaction among factors with an infill setting of 20% and 80% in the case of Experiment-1. All the relevant graphs and charts can be found in the supplementary material.

The ideal configuration was determined by comparing the fitted means from the cube plot to the expected value. The expected value for the height was 30 mm and for base area was 706.8583 mm2. The pareto chart shows the statistically significant factors in Fig. 3. The statistically significant factors indicate that the differences between these groups are not simply due to a chance and are real, this can be said with a confidence level of 95%, since all the obtained data was normally distributed [18,19].

 

Fig. 3 Pareto chart and cube plot of 20% and 80% infill for height (top) and base area (bottom) in Experiment-2.

 

The experimental factors can show effects such as main effect and interaction effects. The main effect is the effect of one factor on the experiment while ignoring the effects by all other factors. It shows how much the average performance of one level differs from the average performance of another level [18,19].

In different settings, different factors show main effect. For example, the plot in Fig. 3 indicates that the infill factor doesn’t show main effect, because the plot is nearly parallel to the central line of average. However, the color and the shape of the object show a significant level of main effect.

In the case of the interaction plot, which shows whether one factor affects another [18,19], the graphs make it very clear that the tendency to interact is high when the lines are intersecting. Henceforth, if two or more factors interact, they are indicated using an asterisk between them.

 

Fig. 4 Main effects and interaction of 20% and 80% infill for height (top) and base area (bottom) in Experiment-1.

 

References

References can be found in the Introduction section.

3D Objects, Engineering, Optimizing 3D Prints, Sustainability

Optimizing 3D Prints- Experiments: X-ray Tomography

Experiments: X-ray Tomography

A powerful technique in determining the internal structure of closed objects is X-ray computed tomography (CT) or simply, tomography or CT scan. A beam of X-rays is projected on the desired specimen. The radiation transmitted by the specimen is captured by an optical receiver. Images are captured for each discrete rotation of the specimen, and they are reconstructed into a 3-dimensional density map. This map can be used to observe the internal structure and determine its flaws and structural inhomogeneity [5,12,16]. It can also be used to determine minute morphological variations. A Bruker Skyscan 1172 Micro-CT scanner was used to perform this experiment. The specimen here is the 3D printed PLA object using the FFF printer. This is placed using a mount and a paraffin film, so that there is no movement. This film is transparent to X-rays.

It was important to choose an appropriate voltage to keep the power supplied very close to 10 W, so that the X-ray source and the transmitted X-rays from the specimen remains high. A low voltage would result in an inefficient capture of images by the receiver [5,16]. The voltage chosen here was 44 kV. The corresponding current was 222 mA.

When objects were scanned, the captured dataset had 631 horizontal cross section and 1000 vertical cross section slices of images. When it came to the scanning the outer shell, 641 images were captured for pink cones and cylinders, whereas 901 images were captured for the transparent cylinders. The resolution of the obtained images was set to 1K (1000 x 666 ppi for the outer shell, 1000 x 632 ppi for the vertical cross section, and 1000 x 1000 ppi for the horizontal cross sections). The images were captured for all 4 infill levels for natural cylinders, and for both pink cones and cylinders.

 

References

References can be found in the Introduction section.

3D Objects, Engineering, Optimizing 3D Prints, Sustainability

Optimizing 3D Prints- Experiments: Statistical Conformity

Experiments: Statistical Conformity

While determining the quality of the 3D printed objects, it was important to make sure that all the prints conformed to the specification. The two measurements of interests were the height of the object and the diameter, as they are required to determine surface area of the objects. When the right-circular cone and right-circular cylinder were modeled, they were designed to have a height and base diameter of 30 mm each. The statistical software, Minitab was used to analyze the data. Three factors were considered.

The first was pigmentation. It is important because it has an influence on the final print-shape. The user always has an option to use colored PLA filament. Adding colored pigments to natural PLA will give it different properties [25]. For an extruder temperature above 493 K (219.85 °C), the pigmentation becomes relevant as it affects the roughness of the final print [23], hence a lower optimal temperature was chosen. The temperature can also alter the printing material’s crystallinity, depending on its color [25], which will, in turn, affect the appearance of the printed object. In this experiment, the colors used were natural (translucent), pink, and blue.

The second factor was the amount of infill. The amount of infill has a range of 0 to 100%. An infill level of 20% and 80% are commonly used [23], and on top of that, the two extreme levels of 0 (hollow) and 100% (solid) were chosen along with them. For a shorter print duration, a lower infill is chosen, for better stability, a higher infill is chosen [23].

Finally, the third was the type of shape/deformation of the object, i.e., whether it gradually tapered (cone), or didn’t (cylinder). There are several other factors which can contribute to the quality of print such as the temperature of the nozzle, size of the nozzle, rate of filament retraction and many more [9,20,21,26]. They are not considered in this experiment.

Once the prints were complete, they were measured using a digital Vernier caliper for accurate measurements, and the grand averages of the values of the height and base diameter were obtained. The area of the base was also calculated. Each experiment was replicated to check for bias. The test used to perform the analysis was Anderson-Darling test using Minitab. The collected data was confirmed to be normal with a 95% confidence interval, as shown in Fig. 2 for cones of 80% infill. Similar data for other infill levels of all objects also exists and is made available in the supplementary material.

Fig. 2 Graphs showing normality of the measurement data in the case of 80% infill level.

 

In Fig. 2, the factor that determines the significance of the result of the normality test is p-value. Since the p-values were higher than 0.05, the data collected is normal and does not have false-positives. The closer the p-value to 1, the more normally distributed is the data [18,19]. It also shows the standard deviation of the data.

Experiment-1 was a 2k factorial design, where k is the number of factors; each factor has two levels. The pigmentation factors were selected to be natural (translucent) and pink, and the shape was tapered or none. Each time the experiment was performed, only a pair of the infill factors was chosen to keep the levels consistent. i.e., a combination of two among hollow, 20%, 80%, and solid were chosen. Depending upon the combination, an appropriate level was chosen to be the lower infill and higher infill level. This was done to determine the optimum levels of infill if the choice were among the combinations. The shape/deformation factor were tapered and none.

Experiment-2 was the same as the first, except the pigmentation was changed from pink to blue. Finally, Experiment-3 factored the colored PLAs (pink and blue) for analysis. Table 1 shows the factors and their associated levels. For simplicity, they are labelled as factors A, B, and C in the table and henceforth.

 

Factor Level 1 Level 2
Factor A (Pigmentation) Color 1 Color 2
Factor B (Infill) Lower Infill Higher Infill
Factor C (Shape) None Tapered

Table 1. Factors and their levels

 

References

References can be found in the Introduction section.

3D Objects, Engineering, Optimizing 3D Prints, Sustainability

Optimizing 3D Prints- Experiments

Experiments

To determine the optimal configuration, two kinds of analyses were performed on 3D printed objects of select shapes or deformation. The deformation here indicates whether the overall shape of the object is tapering or not. The shapes chosen were right circular cylinder and right circular cones. These objects were printed at different levels of infill and with different colors. The colors are referred to as pigmentation, especially in the figures.

The first was a statistical experiment, performed to determine whether the shapes conformed to the specifications. The second was a tomographic scan to determine the variation of structure and the layers of the printed objects.

The printed layer thickness was set to be approximately 200 µm. The printer used was Ultimaker 2+ Extended. It was set to the following settings: nozzle size of 0.4 mm, nozzle temperature set at 210 °C, default build plate temperature of 60 °C, and PLA filament thickness of 2.85 mm. Fig. 1 shows a selection of print samples of different colors, shapes, and infill.

Fig. 1 Print samples from one set of experiment