US 12,222,709 B2
Intent-based automation engineering method
Dirk Schulz, Meckenheim (DE); and Raoul Jetley, Karnataka (IN)
Assigned to ABB Schweiz AG, Baden (CH)
Filed by ABB Schweiz AG, Baden (CH)
Filed on Aug. 31, 2021, as Appl. No. 17/462,017.
Application 17/462,017 is a continuation of application No. PCT/EP2020/056255, filed on Mar. 9, 2020.
Claims priority of application No. 19161637 (EP), filed on Mar. 8, 2019.
Prior Publication US 2021/0397173 A1, Dec. 23, 2021
Int. Cl. G05B 19/418 (2006.01)
CPC G05B 19/41885 (2013.01) [G05B 2219/31368 (2013.01); G05B 2219/42155 (2013.01)] 19 Claims
OG exemplary drawing
 
1. An intent-based automation engineering method for automation of a production process, comprising:
receiving an intent model, correlating to process intent, comprising production process functions, constraints on measurable properties on the production process functions, and/or production process function sequences required for the production process, wherein the intent model comprises automation engineering data, which are recorded using an intent-language that formulates a quantifiable expectation on the behavior of one or more components of the production process;
receiving a process model, correlating to process knowledge comprising a production process behavior, wherein the process model comprises statements on a consequence of the production process behavior, wherein the process model is determined by abstracting the process knowledge, wherein the abstracting comprises converting individual machine-readable expert statements on process knowledge into the process model, and wherein the process knowledge is extracted from existing specifications using pattern recognition algorithms, natural language processing and/or AI-based classification;
determining a machine-readable production model linking the received intent model to the received process model, wherein the production model comprises data associated with maintaining and monitoring a state of the production process and represented at a lower degree of complexity than a degree of complexity of the received process model;
determining a control strategy for controlling the production process dependent on the provided production model; and
adjusting at least one production process step based on the control strategy.