{2024} Geschichte
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©Philomena Famulok
2022
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1996 Pioneer Anime Magazine Ad featuring Tenchi Muyo! Ryo-Ohki
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Trace
22.86 x 17.78 cm
Laser Engraved Woodcut
2022
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Emily Jacir, Where We Come From (Jihad), (chromogenic print and laser print mounted on board), 2001-2003 [SFMOMA, San Francisco, CA. © Emily Jacir]
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Thank you for the email, Reddit.
Me too.
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Researchers from EPFL have resolved a long-standing debate surrounding laser additive manufacturing processes with a pioneering approach to defect detection.
The progression of laser additive manufacturing -- which involves 3D printing of metallic objects using powders and lasers -- has often been hindered by unexpected defects. Traditional monitoring methods, such as thermal imaging and machine learning algorithms, have shown significant limitations. They often either overlook defects or misinterpret them, making precision manufacturing elusive and barring the technique from essential industries like aeronautics and automotive manufacturing. But what if it were possible to detect defects in real time based on the differences in the sound the printer makes during a flawless print and one with irregularities? Up until now, the prospect of detecting these defects this way was deemed unreliable. However, researchers at the Laboratory of Thermomechanical Metallurgy (LMTM) at EPFL's School of Engineering have successfully challenged this assumption.
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WIP Winnie-the-Pooh
Part VI
decorating and titling the case
This cover is a mess of different decoration techniques. There is the depression for an inlay, a laser printed picture of Winnie, the honey pot on the back side is painted on and finally the title was hot stamped.
As a last touch I added the inlay for the balloon and immediately messed up because I cut the marbled paper too small and it looked more egg-like.
So I went fixing it...
Which gave me a differently shaped egg with paper running up the edge of the set back area -_-
So I kept fixing and now it looks pretty balloon-shaped.
If nothing else worked I was prepared to add another, better cut piece of paper. But I liked the little heart in the other cut out, so I really wanted that to work.
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Tested my screens they work very good excited to slap these on stuff and make more designs.
(Underglaze on rice paper)
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{2023} Kollaps
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©Philomena Famulok
mixed media, 2022
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Finally at a stage of actually trialling out this loom (despite all my weaving accoutrements being in storage and reverting to a slapdash cereal box shuttle)! It has a few niggles; namely that the designer clearly doesn’t weave herself, thus didn’t know the practical differences between a 4-shaft and rigid heddle loom, just the cosmetic ones. But unexpected side effect I do love: being able to balance my laptop on top of the whole thing because the shaft controls are on the sides! Wooo!
It works!! Look at that beautiful zigzag pattern.
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Guilty Gear
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as an extension of the halloween costume redesign post i made Once Upon a Time ™️ (not that long ago): jeremy's cyborg eye thing being made of a partial face mask like the phantom of the opera. yes as a reference to his theatre geek side & once again alluding to his connection with christine. (as mentioned in the tags of my og post)
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Researchers at the Department of Energy's Oak Ridge National Laboratory have improved flaw detection to increase confidence in metal parts that are 3D-printed using laser powder bed fusion. This type of additive manufacturing offers the energy, aerospace, nuclear and defense industries the ability to create highly specialized parts with complex shapes from a broad range of materials. However, the technology isn't more widely used because it's challenging to check the product thoroughly and accurately; conventional inspection methods may not find flaws embedded deep in the layers of a printed part.
ORNL researchers developed a method that combines inspection of the printed part after it is built with information collected from sensors during the printing process. The combined data then teaches a machine-learning algorithm to identify flaws in the product. Even more significantly, this framework allows operators to know the probability of accurate flaw detection just as reliably as traditional evaluation methods that demand more time and labor.
"We can detect flaw sizes of about half a millimeter -- about the thickness of a business card -- 90% of the time," said ORNL researcher Luke Scime. "We're the first to put a number value on the level of confidence possible for in situ (in process) flaw detection." By extension, that reflects confidence in the product's safety and reliability.
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