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At least 19 records

The g-code file

The slicing process for additive manufacturing (AM) involves many steps, including slicing the object to be printed and fitting toolpaths to each resulting layer. The toolpaths define the trajectories that the machine must follow during printing to construct the object. Once the slicing is complete and all toolpaths have been found and properly planned, this data must be transferred to the 3D printer in a way the printer can use to construct the object. This is achieved by exporting a file, usually a g-code file, from the slicing software. The g-code file is a text-based file that contains instructions for the machine, controlling the system and defining the motions for each toolpath. The file, which often contains thousands of lines of code, is mostly composed of numbers that command positions for axis motions. This chapter will outline the contents of a g-code file, discuss various commands and their implementation, then provide example codes and files for object construction.

Roschli, Alex↗

FY2022 Square Duct G-Code

The code included in this document was used to create a square duct additive manufacturing build. Questions regarding the code and documentation can be sent to the authors listed.

36 MATERIALS SCIENCE↗

An End-to-End Framework for Verifying and Validating Manufacturing Design Integrity

Cyber attacks on networked automated manufacturing systems can severely impact part quality. In fact, malicious modifications may be introduced at any point during the manufacturing lifecycle. Therefore, it is vital to verify and validate that manufactured parts conform to their designs. This chapter describes a formal, end-to-end framework that verifies and validates the design integrity of manufactured parts by considering all potential points of alteration during precision manufacturing processes. The framework prevents unauthorized changes to computer-aided designs, verifies the correctness of translations from CAD models to G-code, maintains the integrity of G-code transferred to manufacturing machines, verifies the runtime execution of G-code and part geometry, and considers the contexts of manufacturing machine operations and how manufactured parts could be altered.

Jablonski, Matthew [Cybersecurity Manufacturing In↗

ORNL Slicer 2 - Open Source Copyright

ORNL Slicer 2 is a slicing program for additive manufacturing. It takes a solid body mesh object, typically as .STL file, and converts that into machine readable instructions, called g-code, that a 3D printer can use to build the object. The functionality includes loading and positioning an object, slicing it into layers, fitting toolpaths to the layers, and outputting g-code to construct the object. All of this is contained within a graphical user interface (GUI) that allows the user to define all of the settings specific to their machine and process, then preview the resultant g-code before starting the printing process.

Roschli, Alex (0000000213084632)↗

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗

Planar slicing for nonextrusion AM processes

Extrusion-based AM processes, including material extrusion and directed energy deposition, construct objects by continuously depositing a relatively small amount of molten feedstock to a specific location. Nonextrusion AM processes, on the other hand, tend to form each layer by linearly or areally projecting either energy onto a vat of photocurable liquid or a binding agent into a bed of loose powder. Such systems vary significantly from extrusion-based AM processes but do share similarities. The general approach to path planning is the same, but nonextrusion processes typically favor the use of bitmap representations, instead of polygons, for pathing computation and do not use a g-code file to command the printer. In this chapter, a high-level discussion of these differences will be covered.

Macdonald, Eric↗

Cyber-Physical System Implementation for Manufacturing With Analytics in the Cloud Layer

Effective and efficient modern manufacturing operations require the acceptance and incorporation of the fourth industrial revolution, also known as Industry 4.0. Traditional shop floors are evolving their production into smart factories. To continue this trend, a specific architecture for the cyber-physical system is required, as well as a systematic approach to automate the application of algorithms and transform the acquired data into useful information. This work makes use of an approach that distinguishes three layers that are part of the existing Industry 4.0 paradigm: edge, fog, and cloud. Each of the layers performs computational operations, transforming the data produced in the smart factory into useful information. Trained or untrained methods for data analytics can be incorporated into the architecture. A case study is presented in which a real-time statistical control process algorithm based on control charts was implemented. The algorithm automatically detects changes in the material being processed in a computerized numerical control (CNC) machine. The algorithm implemented in the proposed architecture yielded short response times. The performance was effective since it automatically adapted to the machining of aluminum and then detected when the material was switched to steel. The data were backed up in a database that would allow traceability to the line of g-code that performed the machining.

97 MATHEMATICS AND COMPUTING↗

On the optimized 3D printing and post-processing of PETG materials

Glycol-modified polyethylene terephthalate (PETG) is a reliable middle ground between polylactic acid and acrylonitrile butadiene styrene due to its light weight, impact resistance, toughness, flexibility, and cost-effectiveness. However, during 3D printing, the filament form is prone to oozing and stringing. In this study, we optimized the PETG printability via g-code setting and printing parameter modification, and consideration of filament quality, build plate temperature and leveling, and printing design complexity. Printed PETGs were thermally and chemically annealed, and post-processing conditions including annealing time, temperature, and solvent use were investigated. Mechanical properties were evaluated in terms of print parameter changes and post-processing techniques.

36 MATERIALS SCIENCE↗

Slicing Solutions for Wire Arc Additive Manufacturing

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths.

36 MATERIALS SCIENCE↗

Zero Launch Mass Three Dimensional Print Head

NASA's strategic goal is to put humans on Mars in the 2030's. The NASA Human Spaceflight Architecture Team (HAT) and NASA Mars Design Reference Architecture (DRA) 5.0 has determined that in-situ resource utilization (ISRU) is an essential technology to accomplish this mission. Additive construction technology using in-situ materials from planetary surfaces will reduce launch mass, allow structures to be three dimensionally (3D) printed on demand, and will allow building designs to be transmitted digitally from Earth and printed in space. This will ultimately lead to elimination of reliance on structural materials launched from Earth (zero launch mass of construction consumables). The zero launch mass (ZLM) 3D print head project addressed this need by developing a system that 3D prints using a mixture of in-situ regolith and polymer as feedstock, determining the optimum mixture ratio and regolith particle size distribution, developing software to convert g-code into motion instructions for a FANUC robotic arm, printing test samples, performing materials testing, and printing a reduced scale habitable structure concept. This paper will focus on the ZLM 3D Print Head design, materials selection, software development, and lessons learned from operating the system in the NASA KSC Swamp Works Granular Mechanics & Regolith Operations (GMRO) Laboratory.

3D print↗

Zero Launch Mass Three Dimensional Print Head

NASA's strategic goal is to put humans on Mars in the 2030s. The NASA Human Spaceflight Architecture Team (HAT) and NASA Mars Design Reference Architecture (DRA) 5.0 has determined that in-situ resource utilization (ISRU) is an essential technology to accomplish this mission. Additive construction technology using in-situ materials from planetary surfaces will reduce launch mass, allow structures to be three dimensionally (3D) printed on demand, and will allow building designs to be transmitted digitally from Earth and printed in space. This will ultimately lead to elimination of reliance on structural materials launched from Earth (zero launch mass of construction consumables). The zero launch mass (ZLM) 3D print head project addressed this need by developing a system that 3D prints using a mixture of in-situ regolith and polymer as feedstock, determining the optimum mixture ratio and regolith particle size distribution, developing software to convert g-code into motion instructions for a FANUC robotic arm, printing test samples, performing materials testing, and printing a reduced scale habitable structure concept. This paper will focus on the ZLM 3D Print Head design, materials selection, software development, and lessons learned from operating the system in the NASA KSC Swamp Works Granular Mechanics & Regolith Operations (GMRO) Laboratory.

Regolith↗

Fundamental Path Optimization Strategies for Extrusion-based Additive Manufacturing

Extrusion-based additive manufacturing processes begin with a software program, called a slicer, that generates layer geometry and fits toolpaths to each layer to define where material is to be extruded or deposited. Before the toolpaths are output as g-code for the additive manufacturing system to execute, the toolpaths should be optimized. Many complex optimization approaches using graph theory, Chinese postman problem, and other complex mathematical models exist, but these approaches are rarely used in daily printing operations and are not available through common slicing programs such as Cura and PrusaSlicer. Instead, path planning and optimization typically revolves around simpler, fully automated approaches such as inside out and next closest. This paper will explore the fundamental optimization strategies for toolpath planning and document a new implementation, available via open-source slicing software, that allows for greater control of the path planning process.

Roschli, Alex [ORNL] (ORCID:0000000213084632)↗

EG and G and NASA face seal codes comparison

This viewgraph presentation presents the following results for the example comparison: EG&G code with face deformations suppressed and SPIRALG agree well with each other as well as with the experimental data; 0 rpm stiffness data calculated by EG&G code are about 70-100 percent lower than that by SPIRALG; there is no appreciable difference between 0 rpm and 16,000 rpm stiffness and damping coefficients calculated by SPIRALG; and the film damping above 500 psig calculated by SPIRALG is much higher than the O-Ring secondary seal damping (e.g. 50 lbf.s/in).

Basu, Prit↗