Replies to post #11405 on Sigma Labs Inc (SASI)

[Jackle]

It's a fair question.

I think in general i think it is something that companies do need to be very wary of in this part of the world, and ultimately the speed of technological knowledge is snowballing in this part of the world. However i think the Sigma guys have got a massive head start and thus would be more useful inside the tent in order to help set up an asian aerospace industry if something like that would occur. Also, and i think this is important, the aerospace industry globally is both heavily regulated and thus it is harder to cut corners with people's safety. When Comac get's up and running, as it will, it will be an enormous pride to China to compete with the likes of Boeing and Airbus. HUGE. Don't underestimate the milestone this would be to China's development into the global economy. As such any failure or problem would be 'unthinkable'. China is all about face. My impression is that China will spend heavily to make sure the vital parts are under its wing. It's the periphary technology that needs worry more about more local versions. As far as i am concerned Sigma fits into this important proprietary technology and it is something China would love to get it's hands on and be happy to pay for that opportunity.
All this is conjecture at moment, but in many ways this development could make a lot of sense, it does to me.

On top of this, let's not forget Sigma's immediate customer base is in a more patent friendly society. Deals with GE, Boeing, Northrop, Honeywell would see us all in retirement as it is :)

[jjsmith77]

Not really Schris. eoiuheaoidh asked a similar question:

http://investorshub.advfn.com/boards/read_msg.aspx?message_id=95856242

The barrier is the Neural Network, material characteristics, and welding parameters. The neural network is a probabilistic computer that deduces the root cause of "off nominal" signals. The training of the neural network requires user input of material characteristic and welding parameters for normal, off-normal, and unacceptable welds. So, it is quite difficult to create a deduction computer system and train that system with proper parameters of material characteristics and behavior for the system to perform correctly. Also, especially difficult when the system is patented and material characteristics are not well studied.

Acoustic energy was used to dectect:
1. mechanical properties and phenomenon
2. thermal properties and phenomenon
3. metallurgical properties and phenomenon

http://patft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=6857553.PN.&OS=PN/6857553&RS=PN/6857553

http://jjsigmalabsblog.blogspot.com/2013/12/acoustic-energy.html

Then the scientists added inverse thermal models, predicted and actual thermal profiles, and a reduced-order thermal model, all of which comprise a system to accurately detect heat:

http://jjsigmalabsblog.blogspot.com/2013/12/printrite3d-thermal.html

All this requires extensive studies of metal characteristics and behavior for the models to be accurate.

Nonetheless, the end result is a 3D printed part that needs to be tested with current tests for forged parts for an equal playing field. That is the make-or-break factor in trying to copy PrintRite3D.