Additive manufacturing processes, while amazing and valuable, are not without their flaws, and lots of research has been conducted into how and why defects in 3D printing that can cause weakness in printed products, like micro cracking and spattering, occur. One industry that has long adopted additive manufacturing technology is aerospace, and Rolls Royce, one of the world’s top leading manufacturers of jet engines, is no stranger to using AM to make its powerful jet engines. The company uses laser metal deposition (LMD) to 3D print its engine blades out of titanium and nickel powder super alloys. To keep weight down, the blades are arranged in groups called blisks (bladed discs), and when just one blade is damaged due to intense heat and pressure, the entire blisk is removed so the damaged part can be milled off and replaced with a 3D printed one. Rolls Royce is now working at the Diamond Light Source synchrotron in Oxfordshire with AMAZE, a collaboration of 26 European institutions from academia, research, and industry, to get rid of as many AM defects as it possibly can.
“What we have is a storage ring which circulates electrons close to the speed of light,” explained Professor Andrew Harrison, the CEO of Diamond Light Source, about the science behind the synchrotron. “As it goes round the ring the current of electrons gives off a brilliant flash of light in the x-ray part of the spectrum – we use that light to feed instruments that we think of as very high powered microscopes.”
So, why will this flash of light, which is a whopping 10 billion times brighter than the sun, help improve AM processes? It allows scientists to study the structures of materials at the atomic scale, and see how uniformly the layers are forming as they’re deposited. X-ray technology in a regular lab will allow for about 100 frames to be captured in a second – the beam from the synchrotron allows for 10,000.
“You can see molten pools forming and also defects developing during the melt track evolution,” said Alex Leung, an aerospace materials engineer from the University of Manchester, which is one of the AMAZE research partners. “We also see lots of powders that are blowing off – ejecting away from – the powder bed. Some of them may be melt droplets which could add to surface roughness on the additive manufacturing component.”
Leung explained, “You want to make something that is perfectly smooth. You want to get all of the powder into there. Looking at just a single layer may not be representative. What we have done is add more powders onto the layer above and then repeat the process which is exactly what happens in the real-life process.”
The teams from AMAZE and Rolls Royce are working to correlate all of the data that their experiments are producing in order to discover parts of the process that can be measured in commercial industrial additive manufacturing, where they can easily see surface fluctuations.
“The controllable point [of laser metal deposition is] just above the surface, where the laser hits the powder. No one actually knows what happens from then on. We are not really sure whether the laser is melting it on the surface or melting the powder in the air,” said Peter Lee, Professor of Materials Imaging at the University of Manchester and leader of the AMAZE project. “You get powder blowing off the side, you get oscillations in the surface and we are not sure why. We are hoping to make it so for the first time you can see what is happening inside that nozzle.”
“Manufacturers know they will see various fluctuations, but they don’t know what causes them. The goal of this is to say what causes them and then use other lower cost, faster techniques to make better components.”
The team has been working on the project for a year and a half, and will soon be publishing their results; then, Rolls Royce will be able to take what it’s learned and integrate it into its AM processes, to help reduce CO2 emissions and noise on take-off and landing, increase engine performance, and save money by reducing damaged components. A longer term goal of the overall project is creating uniform deposition through closed loop control, using machine learning.
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