Machine learning assistance for industrial automation programming and data environments

A method, comprising:

• providing a programming environment for editing control logic for an industrial automation environment, wherein operational data from the industrial automation environment is accessible from within the programming environment through a data pipeline;
• analyzing, with a machine learning engine, the operational data from the industrial automation environment and the control logic for the industrial automation environment, wherein the machine learning engine is trained to analyze at least the control logic and the operational data in conjunction to detect possible deficiencies and possible improvements in the control logic;
• identifying, with the machine learning engine, a portion of the operational data and a corresponding portion of the control logic;
• generating, with the machine learning engine, a recommendation for the control logic based at least in part on the portion of the operational data and the corresponding portion of the control logic;
• and
• surfacing the recommendation in the programming environment.

A computer-readable memory device having stored thereon instructions that, upon execution by a processing system, cause the processing system to:

• provide a programming environment for editing control logic for an industrial automation environment, wherein operational data from the industrial automation environment is accessible from within the programming environment through a data pipeline;
• analyze, with a machine learning engine, the operational data from the industrial automation environment and the control logic for the industrial automation environment, wherein the machine learning engine is trained to analyze at least the control logic and the operational data in conjunction to detect possible deficiencies and possible improvements in the control logic;
• identify, by the machine learning engine, a portion of the operational data and a corresponding portion of the control logic;
• generate, by the machine learning engine, a recommendation for the control logic based at least in part on the portion of the operational data and the corresponding portion of the control logic;
• and
• surface the recommendation in the programming environment.