China3D printingNet May 28th, the US Army CCDC Army Research Laboratory (ARL) found a prediction3D printingPart performance and understanding of the methods of defects that may affect its performance.
Introduced in detail in a new study, ARL will detect and monitor through sensor measurements3D printingWear of maraging steel. Such measurements can help the military predict when parts will degenerate or fail, and whether they need to be replaced, so that they will remain ready.
” 3D printingThe parts have certain properties due to the manufacturing process itself, and if left unchecked, these parts may degrade in ways that cannot be observed with traditionally machined parts,”CCDC Army Research LaboratoryDr. Jaret C. Riddick, Director of the General Administration of Vehicle Technology explained.
“For this reason, it is generally understood that these parts are used in the current situation only for the purpose of satisfying the Covid-19 response.3D printingIn the process, the key requirements can be met immediately. “
Army researchers studied3D printingThe performance of metal parts and how they degrade are part of ongoing research in vehicle technology. The CCDC Army Research Laboratory at the Aberdeen Proving Grounds in Maryland can print metal parts with powder. Picture courtesy of Dave McNally/US Army.
Army researchers studied3D printingThe performance of the metal parts and how they degrade as part of the ongoing research on in-vehicle technology. The CCDC Army Research Laboratory at the Aberdeen Proving Grounds in Maryland can print metal parts with powder. Picture courtesy of Dave McNally/US Army.
real time monitoring3D printingComponents
The research report is led by the CCDC laboratory, the National Institute of Standards and Technology, CCDC Aeronautics and Missile Center, and the Johns Hopkins University research team. The research report was recently published in the International Journal of Advanced Manufacturing Technology.
It details the use of experimental validation sets to evaluate the use of laser powder bed fusion (LPBF)3D printingThe real-time fatigue behavior of the metal additive manufactured martensitic steel beam produced by the process. Maraging steel is a carbon-free iron-nickel alloy known for its excellent strength and toughness without losing ductility.
Use X-ray computed tomography (CT), nanoindentation and atomic force microscopy to evaluate metal parts. The quasi-static testing process is used to evaluate the printing status.
make sure3D printingThe quality and performance of parts are key requirements for most manufacturers. For example, British engineering company Renishaw (Renishaw) has developed a new software and hardware package designed to improve the quality of LPBF structures through acoustic measurements. Sigma Labs also provides the PrintRite3D in-process quality assurance (IPQA) software package for real-time metal additive manufacturing process monitoring.
Companies such as Siemens use Digital Twins to fully virtualize their development and machine processes to achieve real-time monitoring of production performance.
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3D printingMetal parts. Image courtesy of the US Army/David McNally.
Make sure the army is ready to proceed3D printingdeploy
Dr. Riddick explained that the ARL study points to a verification process that ensures readiness in environments where replacement parts are urgently needed, thereby limiting the time to deliver parts from a distance. In this case, soldiers usually choose expedient measures to continue the mission rather than suspend the mission altogether.
The co-author of the study, Dr. Todd C. Henry, a mechanical engineer in the laboratory, likened the clues given by the verification kit about the material performance to a vehicle odometer reading, which indicates the need for an oil change: the eddy current sensor will provide the measured value, and Let you know which parts need to be replaced. “ HenryThe PhD also hopes to develop a tool to measure each3D printingThe unique properties of the components and the recognition that each component measured by the sensor is different.
usually,3D printingThe defects of the part are due to the gaps and geometric differences between the computer model and the printed part. The sensor technology developed by ARL provides a way to track individual parts, predict the point of failure, and replace them for several cycles before damage.
According to China3D printingNet understands that Army researchers applied these findings to the3D printingIn the new research on stainless steel parts, machine learning technology is used instead of sensors to characterize the life of the parts.3D printingWith cost and time advantages, you may still need to use it anyway. Imagine a situation where you always choose the strongest material, but there is another material that is cheaper and easier to obtain, but you need to prove that you can rely on other materials.
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