US 12,326,699 B2
Data scientist views in integrated design environments
Jordan C. Reynolds, Austin, TX (US); John J. Hagerbaumer, Mequon, WI (US); Troy W. Mahr, Pleasant Prairie, WI (US); Thomas K. Jacobsen, Wake Forest, NC (US); and Giancarlo Scaturchio, Pisa (IT)
Assigned to Rockwell Automation Technologies, Inc., Mayfield Heights, OH (US)
Filed by Rockwell Automation Technologies, Inc., Mayfield Heights, OH (US)
Filed on Jun. 28, 2022, as Appl. No. 17/851,628.
Prior Publication US 2023/0418243 A1, Dec. 28, 2023
Int. Cl. G06F 9/451 (2018.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01); G06F 8/34 (2018.01); G06F 8/35 (2018.01); G06F 9/44 (2018.01)
CPC G05B 13/0265 (2013.01) [G06F 8/34 (2013.01); G06F 8/35 (2013.01); G06F 9/44 (2013.01); G05B 13/027 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system to surface machine learning systems in a design application of an industrial automation environment, the system comprising:
a memory that stores executable components; and
a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising:
a design component configured to generate a control program configured for implementation by a Programmable Logic Controller (PLC) and receive a user input that selects a program tag that represents a target variable in an industrial automation process;
in response to the user selection, the design component configured to identify one or more machine learning models associated with the target variable and display the one or more machine learning models;
the design component configured to receive a user input that selects one of the one or more machine learning models and responsively integrate another program tag that represents the selected machine learning model into the control program;
the design component configured to receive another user input to generate a new machine learning model for the selected program tag;
a machine learning interface application configured to:
generate feature vectors that represent the target variable; and
train the new machine learning model based on the feature vectors; and
the design component configured to generate a new program tag that represents the new machine learning model and integrate the new program tag into the control program.