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AMT Tech Report: Issue #285

Everyone has a dirty secret. Is AI in manufacturing? Why do we need humanoid robots? Time to reinvent electromagnetic coils. Trust but verify ... your training models.
Nov 10, 2023

Things which do not grow and change are dead things.

Louise Erdrich


1. Everyone Has a Dirty Secret

Additive has more skeletons in its closet than people think. Yes, you can grow parts that radically improve end users' productivity and output, but the path to achieving that goal? It can be a little glossed over. Additive processes require a significant amount of removal, including powder, support, base, and finishing.   

Read more here.


2. Is AI in Manufacturing?

Yes, it always has been. However, this concept is changing quickly in this day and age. Previously, AI was heavily used in automation and metrology. Now we are seeing more companies use AI in supply chain, quality control, and predictive maintenance, areas where larger companies had already been leveraging this tool. The industry can learn quickly from these early adopters. 

Read more here.


3. Why Do We Need Humanoid Robots?

As much as I am a technologist, humanoid robots still don't seem efficient. China, however, thinks that humanoid robots are the future and plans on mass producing the technology. There is some validity to this plan, which outlines guidelines reflecting different parts of the robot, such as brains (control) and limbs (end-of-arm tooling). I'll warm up some popcorn and see how this plays out – mass adoption? Or lost in time … like tears in rain?  

Read more here.


4. Time To Reinvent Electromagnetic Coils

The demand for electromagnetic coils will only continue to grow. This growth is due to the EV and hybrid market and the significant growth of industrial applications. As we have seen in gas applications, applying additive processes to electromagnetic fields could yield increased efficiency and power. 

Read more here.


5. Trust but Verify ... Your Training Models

So, the source of training models is coming under heavy scrutiny. There is a lot of discussion on the legality of mass scraping copyrighted material. As a result, groups are creating tools to "poison" training data. Why is this important to manufacturing? Some datasets are publicly available, and it is worth assessing the validity of these datasets.

Read more here.

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Author
Benjamin Moses
Director, Technology
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