Predictive maintenance and process supervision using a scalable industrial analytics platform

A method, comprising:

• receiving, by a system comprising a processor, data files from industrial devices and systems at one or more industrial facilities, wherein the data files accord to different file formats;
• generating, by the system, relationship metadata identifying correlations between data items contained in the data files;
• storing, by the system, the data items in association with the relationship metadata;
• identifying, based on an analysis of a first subset of the data items and a first subset of the relationship metadata, ranges of performance metrics of the industrial devices and systems that correlate with a defined production outcome over multiple production cycles;
• generating performance model data that records the ranges of the performance metrics;
• identifying the performance issue based on a comparison of the performance model data with a second subset of the data items and a second subset of the relationship metadata received subsequent to the first subset of the data items and the first subset of the relationship metadata;
• and
• generating performance model data that records the ranges of the performance metrics;
• identifying a performance issue associated with one or more of the industrial devices and systems based on a comparison of the performance model data with a second subset of the data items and a second subset of the relationship metadata received subsequent to the first subset of the data items and the first subset of the relationship metadata;
• and
• sending, by the system, a dashboard interface to a client device, wherein the dashboard interface displays a notification of the performance issue and a recommended countermeasure determined to mitigate the performance issue.

A non-transitory computer-readable medium having stored thereon executable components that, in response to execution, cause a system comprising a processor to perform operations, the operations comprising:

• receiving data files from industrial devices and systems at one or more industrial facilities, wherein the data files accord to different file formats;
• identifying correlations between data items contained in the data files;
• generating relationship metadata recording the correlations;
• storing the data items in association with the relationship metadata;
• identifying, based on an analysis of a first subset of the data items and a first subset of the relationship metadata, ranges of performance metrics of the industrial devices and systems that correlate with a defined production outcome over multiple production cycles;
• generating performance model data that records the ranges of the performance metrics;
• identifying a performance issue associated with one or more of the industrial devices and systems based on a comparison of the performance model data with a second subset of the data items and a second subset of the relationship metadata received subsequent to the first subset of the data items and the first subset of the relationship metadata;
• and
• rendering a dashboard interface on a client device, wherein the dashboard interface displays a notification of the performance issue and a recommended countermeasure determined to mitigate the performance issue.