Patent ID: 11868932
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Chemical engineering (Chemistry)
Classification: CPC G  B | IPC G

Claim 0:
1. A computer-implemented method comprising:
extracting, by one or more processors, a set of features from time series data generated from one or more sensors, through autoencoding using a neural network, based on one or more non-control variables for the time series data, the one or more non-control variables defining a lack of control by a user on the time series data;
monitoring, by one or more processors, the time series data generated from the one or more sensors;
identifying, by one or more processors, one or more operational modes based on the extracted features including a dimensional reduction with a representation learning from the time series data;
identifying, by one or more processors, a neighborhood of a current operational state based on the extracted features, the neighborhood being a dynamic mode within a same operational mode;
comparing, by one or more processors, the current operational state to one or more historical operational states based on the time series data at the same operational mode of the one or more operational modes;
discovering, by one or more processors, an operational opportunity based on the comparison of the current operational state to the one or more historical operational states using the neighborhood;
identifying, by one or more processors, one or more control variables in the same mode which variables are relevant to the current operational state, the one or more control variables defining actions that can be controlled by the user; and
recommending, by one or more processors, an action strategy based on the one or more control variables, the one or more non-control variables, and a target productivity.