Process control system using spatially dependent data for controlling a web-based process

A method for controlling a web-based manufacturing process with spatially dependent conditions for producing a web product with spatially dependent properties, comprising:

• synthesizing, via a machine learning method, one or more process conditions at each of one or more spatial positions in a production line of a web-based manufacturing process or synthesizing one or more web product properties at each of one or more spatial positions on the web product to generate input data, wherein synthesizing comprises generating additional input data using nonlinear models based on historical spatial relationship data;
• providing the input data to a process control system, wherein the input data comprise a plurality of input data sets, each input data set comprising values for a set of one or more input parameters;
• and
• generating output data in accordance with the input data, wherein the output data comprise a plurality of output data sets, each output data set comprising values for a set of one or more output parameters, each output parameter comprising a predicted process condition or web product property, wherein the output data preserve spatial relationships of the output data corresponding to the spatial relationships of the input data, and wherein the output data are useable by the process control system or an operator to control the web-based manufacturing process.

A system for controlling a process with spatially dependent conditions for producing a product with spatially dependent properties, comprising:

• a processor;
• and
• a memory coupled to the processor that stores program instructions executable by the processor to implement a process control system, wherein the process control system comprises:
• a plurality of inputs, operable to receive input data, wherein the input data comprise a plurality of input data sets, each comprising values for a set of one or more input parameters, and wherein the input data are provided by one or more of:
• synthesizing, via a machine learning method, one or more process conditions at each of one or more spatial positions in a production line of the process to generate the input data, or synthesizing one or more product properties at each of one or more spatial positions on the product to generate the input data, wherein synthesizing comprises generating additional input data using nonlinear models based on historical spatial relationship data;
• wherein the process control system is operable to generate output data in accordance with the input data, wherein the output data comprise a plurality of output data sets, each output data set comprising values for a set of one or more output parameters, each output parameter comprising a predicted process condition or product property, wherein the output data preserve spatial relationships of the output data corresponding to the spatial relationships of the input data.