Systems and methods for learning data patterns predictive of an outcome

A system for data collection in an industrial environment, the system comprising:

• a data collector communicatively coupled to a plurality of input channels, wherein the data collector collects data from the plurality of input channels based on a selected data collection routine, wherein each input channel is connected to a monitoring point from which data is collected, wherein the collected data provides a plurality of detection values including detection values for a component of a plurality of components or a subprocess of the industrial environment;
• a machine learning circuit structured to:
• receive a training set of detection values and corresponding outcomes;
• learn data patterns in the set of detection values of the received training set indicative of the corresponding outcomes;
• and
• train a neural net on the learned data patterns;
• a data storage structured to store a plurality of collector routes and collected data that corresponds to the plurality of input channels, wherein the plurality of collector routes each comprises a different data collection routine;
• a data acquisition and analysis circuit structured to interpret the plurality of detection values from the collected data and structured to determine, using the trained neural net, a future status of the component or the subprocess, wherein the future status of the component or the subprocess comprises at least one of:
• a future state of the component, a future condition of the component, or a future stage of the subprocess;
• and
• an analysis response circuit structured to perform an action in response to the determination of the future status of the component or the subprocess, wherein the component includes a motor, wherein the action comprises rebalancing operating work loads of the plurality of components associated with the subprocess by changing an operating parameter of the plurality of components including changing an operating speed of the motor to place the motor in a lower demand mode for at least one of the plurality of components,
• wherein the changing the operating parameter including the changing the operating speed of the motor to place the motor in the lower demand mode extends a first maintenance interval of the motor to synchronize the first maintenance interval of the motor with a second maintenance interval of another one of the plurality of components such that the first maintenance interval is concurrent with the second maintenance interval.

A computer-implemented method for data collection in an industrial environment, the method comprising:

• collecting data from a plurality of input channels communicatively coupled to a data collector based on a data collection routine, wherein each input channel is connected to a monitoring point from which data is collected, wherein the collected data provides a plurality of detection values including detection values for at least one of a plurality of components or a subprocess of the industrial environment, and wherein the at least one of the plurality of components includes a motor of the industrial environment;
• receiving a training set of detection values and corresponding outcomes;
• learning patterns of detection values in the training set indicative of the corresponding outcomes;
• training a neural net on the learned patterns;
• analyzing, utilizing the trained neural net the plurality of detection values from the collected data to determine a future status of the motor, the at least one of the plurality of components, or the subprocess of the industrial environment, wherein the future status of:
• the at least one of the plurality of components, or the subprocess comprises at least one of:
• a future state of the motor, the at least one of the plurality of components,
• a future condition of the motor, the at least one of the plurality of components, or
• a future stage of the subprocess;
• and
• performing an action in response to the determination of the future status of:
• the motor, the at least one of the plurality of components, or the subprocess,
• wherein the at least one of the plurality of components includes a variable speed motor,
• wherein the action comprises changing an operating parameter including changing an operating speed of the variable speed motor to lower a demand on the variable speed of the at least one of the plurality of components, and
• wherein the lowering the demand on the variable speed motor extends a first maintenance interval of the motor to synchronize the first maintenance interval of the motor with a second maintenance interval of another one of the plurality of components such that the first maintenance interval is concurrent with the second maintenance interval.