US 12,034,742 B2
Dynamic monitoring and securing of factory processes, equipment and automated systems
Matthew C. Putman, Brooklyn, NY (US); John B. Putman, Celebration, FL (US); Vadim Pinskiy, Wayne, NJ (US); Damas Limoge, Brooklyn, NY (US); Andrew Sundstrom, Brooklyn, NY (US); and James Williams, III, New York, NY (US)
Assigned to Nanotronics Imaging, Inc., Cuyahoga Falls, OH (US)
Filed by Nanotronics Imaging, Inc., Cuyahoga Falls, OH (US)
Filed on Jun. 23, 2021, as Appl. No. 17/304,614.
Application 17/304,614 is a continuation of application No. 16/781,193, filed on Feb. 4, 2020, granted, now 11,063,965.
Claims priority of provisional application 62/950,588, filed on Dec. 19, 2019.
Prior Publication US 2021/0320931 A1, Oct. 14, 2021
Int. Cl. G05B 19/4155 (2006.01); G06N 3/08 (2023.01); H04L 9/40 (2022.01)
CPC H04L 63/1416 (2013.01) [G05B 19/4155 (2013.01); G06N 3/08 (2013.01); G05B 2219/31372 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A manufacturing system, comprising:
two or more process stations, wherein a first process station is logically positioned upstream of a second process station, wherein each of the first process station and the second process station is configured to perform a step of a multi-step manufacturing process;
a first station controller programmed to control a first operation of the first process station;
a second station controller programmed to control a second operation of the second process station;
a deep learning controller in communication with the two or more process stations, the first station controller, and the second station controller, wherein the deep learning controller is trained to identify anomalous activity in the multi-step manufacturing process based on response data received from the first station controller or the second station controller; and
a signal splitter positioned between the first station controller and the deep learning controller, the signal splitter having a single input, a first output, and a second output, wherein the signal splitter is configured to receive a control value signal output from the first process station via the single input, divide the control value signal output, provide a first instance of the divided control value signal output to the first station controller via the first output and, provide a second instance of the divided control value signal output to the deep learning controller via the second output.