3D Printer Tech Cuts Paper

While 3D printing has been a great thing all by itself, it has also made electromechanical hardware a commodity item. Instead of raiding an old printer for motors and rods of unknown provenance, you can now buy everything very inexpensively due to the economy of scale and offshore manufacturing.

[Mr. Innovation] proves this point with his recent paper cutting machine which feeds and slices paper strips with user-selected width and quantity. He did steal one roller assembly from an old printer, but most of it is straight out of a 3D printer build. There’s NEMA stepper motors, modular motor driver boards, smooth rods, belts, and pulleys.

The blade of the cutter is just a standard snap off box cutter blade. It is angled so it doesn’t drag when the motor pulls it back to the home position after a cut. Honestly, we might have made the paper mechanism retract the paper a bit at that point, but that would be simple to add to the device’s firmware.

You might think an automated paper cutter is a bit lazy, but we could see if you were cutting up flyers for a hackerspace event, or cutting paper insulators to fit in an enclosure for a kit you were selling in small quantities.

The biggest issue we saw was that the machine is open loop. It would have been interesting to put an optical sensor between the roller and the blade. When the paper covered the sensor you’d know the position of the edge and could then move the paper a precise amount, assuming it didn’t slip. Another idea would be to put the sensor after the blade in such a way that it could be moved so that the cut would happen once the paper covered the sensor. You could probably do the same thing with a microswitch or some other sensor.

Still, this looks like a simple but useful project for some leftover 3D printer parts. Just be careful with the open blade.

We couldn’t help but think about building this with a floppy disk blade for cutting plastic. Or you could mount a laser (but use a different power supply, please).

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Novel Approach to Optimizing Soft Material 3D Printing Detailed in New Research Paper

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When it comes to 3D printing materials, from metals and self-folding plastics to biomaterials like soft tissue, the researchers at Carnegie Mellon University (CMU) know their stuff. Now, a research team from the university’s College of Engineering has created a novel approach to optimizing soft material 3D printing, which can be tricky due to the fact that many parameters can affect the final product, such as the consistency of the gel bath an object is printed in, how fast the 3D print head moves, and the concentrations of each material.

Most experimental designs or optimization models will focus on the few parameters deemed most important to the particular print, but it can be tough to adapt these models for experimental materials, as the 3D printing characteristics are often not well-known.

“When 3-D printing thermoplastics, if you have just five or 10 main print parameters and want to explore, say, five levels of each, a factorial design can result in millions of possible combinations of settings to print. The combinations become even more daunting when exploring an experimental material whose print characteristics are unknown,” said Sara Abdollahi, a CMU biomedical engineering PhD student. “For example, if the experimental material has 20 print parameters with five levels, the experimenter can have trillions of combinations of print settings to explore.”

The research team, which consists of Abdollahi, assistant professor of engineering and public policy Alexander Davis, CMU’s Dietrich College of Humanities and Social Sciences Professor John H. Miller, and Adam Feinberg, associate professor of biomedical engineering and materials science and engineering, published a paper on their work, titled “Expert-guided optimization for 3D printing of soft and liquid materials,” in PLOS One. The paper demonstrates their new Expert-Guided Optimization (EGO) method, which was designed to optimize high quality, soft material 3D prints.

Using the EGO found optimum to 3D print epoxy and PDMS in complex geometries. L-R: 3D prints with standard PLA, epoxy, and PDMS.

The abstract reads, “Here, we developed an expert-guided optimization (EGO) strategy to provide structure in exploring and improving the 3D printing of liquid polydimethylsiloxane (PDMS) elastomer resin. EGO uses three steps, starting first with expert screening to select the parameter space, factors, and factor levels. Second is a hill-climbing algorithm to search the parameter space defined by the expert for the best set of parameters. Third is expert decision making to try new factors or a new parameter space to improve on the best current solution. We applied the algorithm to two calibration objects, a hollow cylinder and a five-sided hollow cube that were evaluated based on a multi-factor scoring system. The optimum print settings were then used to print complex PDMS and epoxy 3D objects, including a twisted vase, water drop, toe, and ear, at a level of detail and fidelity previously not obtained.”

Images of the PDMS 3D prints made using the S3D CAD slicer to determine toolpath. [Image: CMU]

The researchers use a 3D printing method known as freeform reversible embedding (FRE), where soft materials are deposited in a gel support bath. As previously mentioned, while typical models and designs only focus on a few select 3D printing parameters, the EGO method can quickly and efficiently rule out any ineffective combinations. It pairs expert judgment with an efficient optimization algorithm to find combinations that will result in optimal, high-fidelity 3D prints for experimental, soft materials.

For the purposes of the paper, the researchers demonstrated their EGO method using liquid polydimethylsiloxane (PDMS) elastomer resin. PDMS is also known as silicone rubber, and is often used in medical devices and wearable sensors.

The team’s innovative EGO method could even extend beyond 3D printing soft materials to multiple engineering processes, and has the potential to be used as a systematic tool for discovering important parameters that lead to high-quality, reproducible, novel materials.

Davis explained, “The purpose of EGO is to create an effective search algorithm that explicitly combines both expert knowledge and traditional search algorithms. Typically we think of machine learning being useful for big data, but EGO works in situations when we have little or no data and need to rely on expert judgment, then through a combination of search algorithms and the expert’s knowledge, effectively transition from small to big data.”

Parameter spaces for 3D printing soft materials using FRE. Five parameter spaces determine the 3D print outcome: physical parameters, printer hardware, model design, model geometry, and print parameters. These last three are inputs used by the slicer algorithm to determine the extruder toolpath and material deposition rate. Print parameters and physical parameters are considered throughout the EGO strategy. The printer hardware and model properties (design and geometry) are relatively time intensive to alter quickly and are often preset as design criteria.

The EGO model is made up of three steps, starting with a human expert choosing the initial set of parameters – this gives the algorithm its search boundaries. A hill-climbing algorithm then searches within these boundaries for any positive combinations of the selected parameters, which will result in a local optimum.

Then, the expert will evaluate this local optimum, and determine whether or not to change the search process by adding additional parameters, or to keep searching within the original boundaries. This three-step process will repeat until the algorithm finds an ideal solution.

Discuss this and other 3D printing topics at 3DPrintBoard.com or share your thoughts in the comments below.

[Sources: CMU, Devdiscourse]

Ocamo Greeting Card 3D Printer Paper Carving Peacock Greeting Card DIY Holiday Card for Mother’s Day Retro envelope -Green

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Michigan Tech Researchers Publish Paper on New Recyclebot 3D Printer

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If you’re familiar with 3D printing, solar power, and open source research, then you’ve probably heard of Dr. Joshua Pearce, Associate Professor of Materials Science & Engineering, and Electrical & Computer Engineering, at Michigan Technological University (Michigan Tech).

Dr. Pearce works to educate the industry as much as he does his students, and has participated in several studies and projects regarding at-home 3D printing, the amount of IP protection in the industry, 3D printers powered by solar energy, metal 3D printing, and RepRap 3D printers, as well as open source software and hardware, among others. He also runs the university’s Open Sustainability Technology (MOST) Research Group.

RepRapable Recyclebot switches.

Dr. Pearce is a major proponent for sustainability, and has also studied filament recycling in the past. In the 2017 study, Dr. Pearce and the rest of his team discussed the development of a solar-powered version of the open source “recyclebot,” an extruder for waste plastic that he designed back in 2013.

It’s expensive to recycle plastic, and also wastes a lot of energy, as it needs to be transported to a central location and separated. The recyclebot could help reduce the energy and cost by collecting plastic waste and recycling it into 3D printer filament on-site.

“As you know 3D printing filament is still sold for far more than plastic pellets and several companies offer filament makers. There has also been some efforts to make recyclebots, that can make filament from waste plastic,” Dr. Pearce told 3DPrint.com this week. “We have developed a new version of the recyclebot with enough control to produce commercial grade filament from more or less anything – we have demonstrated it with pellets, regrind, and even waste composites. The plans are fully open source and most of the parts of the new machine design are themselves 3D printable.”

In a new paper, titled “RepRapable Recyclebot: Open source 3-D printable extruder for converting plastic to 3-D printing filament,” Dr. Pearce and his team relay their continued development of the innovative recyclebot, including the full plans, list of parts, and assembly instructions for the device, which was designed for FFF 3D printer-based filament research.

The abstract reads, “In order to assist researchers explore the full potential of distributed recycling of post-consumer polymer waste, this article describes a recyclebot, which is a waste plastic extruder capable of making commercial quality 3-D printing filament. The device design takes advantage of both the open source hardware methodology and the paradigm developed by the open source self-replicating rapid prototyper (RepRap) 3-D printer community. Specifically, this paper describes the design, fabrication and operation of a RepRapable Recyclebot, which refers to the Recyclebot’s ability to provide the filament needed to largely replicate the parts for the Recyclebot on any type of RepRap 3-D printer. The device costs less than $700 in mate rials and can be fabricated in about 24 h. Filament is produced at 0.4 kg/h using 0.24 kWh/kg with a diameter ±4.6%. Thus, filament can be manufactured from commercial pellets for <22% of commercial filament costs. In addition, it can fabricate recycled waste plastic into filament for 2.5 cents/kg, which is <1000X commercial filament costs. The system can fabricate filament from polymers with extrusion temperatures <250 °C and is thus capable of manufacturing custom filament over a wide range of thermopolymers and composites for material science studies of new materials and recyclability studies, as well as research on novel applications of fused filament based 3-D printing.”

(L-R) Comparison between 3D printed products made from recycled PLA (made), virgin PLA (made), and virgin PLA ( purchased).

According to the paper, the annual worldwide plastic production was 322 million tons in 2015, and that number has been growing 3.86% per year. Incinerating plastic waste, or filling landfills with it, isn’t doing much to help the problem.

“Thus, recycling, is now established in the circular economy as the optimum treatment of post-consumer plastics,” the paper reads. “Unfortunately, there can be significant environmental impacts from the collection and transportation of relatively low-density waste plastics to collection centers and reclamation facilities for separation and reconstruction in traditional recycling.”

Previous research on the recyclebot process using post-consumer plastics shows a decrease of 90% in the embodied energy of the filament when compared to conventional methods of manufacturing, and allows consumers to recycle plastic into 3D printing filament in the comfort of their own home. The paper states that the desktop RepRapable Recyclebot can mostly be made from its own output on any RepRap-based 3D printer, and all of the parts can be easily sourced online or from local hardware stores.

Collected parts ready for assembly.

Co-authors of the paper include Michigan Tech’s Aubrey L. Woern, Joseph R. McCaslin, Adam M. Pringle, and Dr. Pearce.

Discuss this and other 3D printing topics at 3DPrintBoard.com or share your thoughts below.