A Method for Evaluating the Quality of 3D-Printing Metal Parts

A recent poll in Britain found that public support for sanctions against Russia is falling as fuel and prices rise.  

The proportion of people willing to accept higher fuel prices as a result of western sanctions against Russia fell 14 percentage points to 36% from 50% in March, according to a survey conducted for the Telegraph by consultancy Redfield & Wilton Strategies.  

Global energy and fuel prices have soared since the start of the year and remain high because of the conflict between Russia and Ukraine and uncertainty over Russian supplies.  

The survey also found that 54% of people believe their own financial situation has worsened in the past year, up 12 percentage points from 42% two months ago. Sixty-two percent think things will get worse in the year ahead. Less than a third of respondents said they had received a pay rise to keep up with inflation, with two-thirds of those saying it was not enough to keep up with rising living costs.  

The figures suggest that public concern about the conflict with Ukraine is now likely to be overtaken by financial worries.  

Separately, the UK's consumer price index rose 7 percent this month from a year earlier, the highest since March 1992, according to figures released recently by the Office for National Statistics. In addition, a separate report released a few days ago by the Centre for Economics and Business Research said that real household disposable income in the UK will fall by 3% in 2022, equivalent to a loss of £2,320 per household, which would lead to the biggest drop in living standards since the 1950s. That is mainly because wages aren't keeping up with rising energy and fuel costs.  

The prices of other commodities like the 3D printing metal powder are also expected to be influenced.

Researchers at NTU Singapore have developed a fast and low-cost imaging method for assessing the quality of 3D-printed metal parts. This method can analyze the structure and material quality of 3D-printed metal parts. 
 
Most 3D-printed metal alloys consist of numerous microscopic crystals that vary in shape, size, and orientation of the atomic lattice. By mapping this information, scientists and engineers can infer the alloy's properties, such as strength and toughness. It's like looking at wood grain. When wood grain is continuous in the same direction, strength and toughness are strongest.
 
The new technology could benefit the aerospace sector - enabling low-cost rapid assessment of turbines, fan blades, and other critical components, which is of great significance to the maintenance and overhaul industry. 
 
Until now, however, analyzing the "microstructure" in 3D-printed metal alloys has been a time-consuming and laborious process, usually achieved using measurements made with scanning electron microscopes, which cost between S $100,000 and S $2 million. 
 
But the new alloy imaging method developed by Assistant Professor Matteo Seita and his team at NTU provides quality analysis in just a few minutes. They used a system of optical cameras, flashlights, and laptops that ran proprietary machine learning software developed by the team at a total cost of about $25,000.
 
The method involves treating the metal surface with chemicals to reveal its microstructure, then holding the sample facing the camera and using a flashlight to illuminate the metal in different directions to take multiple optical images. The software then analyzes the patterns produced by the light reflected off the surfaces of different metal crystals and deduces their orientation. The whole process takes about 15 minutes. The team's findings have been published in NPJ Computational Materials.
 
"By using our low-cost and fast imaging method, we can easily tell the difference between good 3D-printed metal parts and defective parts. Currently, it is impossible to tell the difference unless we evaluate the microstructure of the materials in detail, "explained Seita, an assistant professor at NTU's School of Mechanical and Aerospace Engineering and School of Materials Science and Engineering. 
 
"Even though two 3D-printed metal parts may be produced using the same technology and have the same geometry, they are never the same. In theory, this is similar to how two originally identical wooden objects could have different texture structures." 
 
New imaging methods improve 3D printing certification and quality assessment.  Assistant Professor Seita believes their innovative imaging method could simplify the certification and quality assessment of metal alloy parts produced by 3D printing, also known as additive manufacturing.
 
One of the most common techniques for 3D printing metal parts is to use high-powered lasers to melt metal powders and fuse them layer by layer until a complete product is printed. 
 
However, the microstructure, and thus the quality of the printed metal, depends on many factors, including the speed or strength of the laser, how long the metal cools before the next layer is melted, and even the type and brand of metal powder used. This is why the same design printed by two different machines or production plants may result in parts of different quality. 
 
Instead of using a complex computer program to measure crystal orientation in the light signals collected, the "smart software" developed by Assistant Professor Seita and his team uses a neural network to simulate how the human brain forms associations and processes thoughts. The team then used machine learning to program the software to feed it hundreds of optical images. 
 
Their software eventually learned how to predict the orientation of crystals in metal from an image, depending on how light scatters from the metal's surface. A complete "crystal orientation diagram" is then created, which provides comprehensive information about crystal shape, size, and atomic lattice orientation.
 
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China's non-manufacturing purchasing managers index for March was released by the China Federation of Logistics and Purchasing and the Service Industry Survey Center of the National Bureau of Statistics today. An index of business activity for the non-manufacturing sector as a whole fell below 50 percent. 

 China's non-manufacturing business activity index was 48.4%, down 3.2 percentage points from the previous month. The new orders index was 45.7 percent, down 1.9 percentage points from the previous month, indicating a significant slowdown in the growth of supply and demand in the non-manufacturing sector from the previous month.   In terms of sectors, the business activity index and new order index of transportation, accommodation and catering, culture, sports and entertainment, and tourism-related industries all declined significantly from the previous month. 

Then the 3D printing metal powder of the market may be affected by significant changes, the price will also be volatile, if you want to know the latest news of the 3D printing metal powder, welcome to contact us. 

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