US 12,140,915 B1
Generative AI and agentic AI systems and methods for industrial equipment and manufacturing systems analytics, control, and optimization
Brian McCarson, Tempe, AZ (US)
Filed by Brian McCarson, Tempe, AZ (US)
Filed on May 14, 2024, as Appl. No. 18/664,045.
Application 18/664,045 is a continuation in part of application No. 18/342,461, filed on Jun. 27, 2023, granted, now 12,093,311.
Int. Cl. G05B 13/04 (2006.01); G05B 13/02 (2006.01)
CPC G05B 13/042 (2013.01) [G05B 13/0265 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A generative artificial intelligence (AI) system for manufacturing systems, comprising:
a plurality of data sources, wherein at least one of the data sources is sensor data derived from direct observation of activity within an environment, including at least a behavior of a manufacturing system;
a context-aware AI database;
a probationary database;
an analytics engine communicatively coupled to the plurality of data sources, the context-aware AI database, and the probationary database;
wherein the analytics engine is configured to:
(a) generate a hypothesis object comprising independent variables, a dependent variable including a leading indicator of manufacturing system behavior, a machine learning model trained from available data, and metadata associated therewith based on the data sources, wherein the leading indicator includes a recommendation or action related to at least one of: control of the industrial equipment, fleet of industrial equipment, manufacturing system, optimization of the manufacturing system, troubleshooting of the manufacturing system, and optimization of the manufacturing system;
(b) train the machine learning model associated with the hypothesis object to produce experimental results;
(c) store the hypothesis object and the experimental results in the context-aware AI database in response to determining that the performance metric of the machine learning model meets a predetermined performance criterion;
(d) store the hypothesis object and the experimental results in the probationary database in response to determining that the performance metric of the machine learning model does not meet a predetermined performance criterion; and
a publishing module configured to provide, to one or more subscribers, the leading indicator associated with at least one of the manufacturing system, a corporate entity associated with the manufacturing system, and a product associated with the corporate entity, as computed by the trained machine learning model stored within the context-aware AI database while processing contemporaneous information received from the data sources.