Methods and arrangments for process analytical technology management and operation

An apparatus comprising:

• a memory;
• processing circuitry coupled with the memory to perform operations to establish monitoring for a Critical Quality Attribute (CQA) in real-time for an in-line instrument of a manufacturing process, the operations to:
• establish one or more parameters for collecting measurement data from the in-line instrument, wherein the measurement data comprises an array of raw data per measurement;
• select a machine learning model for the in-line instrument from a library of machine learning models, based on the manufacturing process and a stage of the manufacturing process associated with an interconnection of the in-line instrument with the manufacturing process, to generate a prediction for the CQA based on data collected from the in-line instrument;
• collect, based on the one or more parameters, the measurement data in real-time from the in-line instrument;
• process the measurement data from the in-line instrument to generate real-time transformed data for the CQA and to predict a model output, the model output comprising trending data for the CQA;
• and
• store the trending data in a data storage device.

A non-transitory computer readable medium comprising instructions, which, when executed by any one or more processors in one or more computers, cause the one or more processors in the one or more computers to perform operations to establish monitoring for a Critical Quality Attribute (CQA) in real-time for an in-line instrument of a manufacturing process, the operations to:

• establish one or more parameters for collecting measurement data from the in-line instrument, wherein the measurement data comprises an array of raw data per measurement;
• select a machine learning model for the in-line instrument from a library of machine learning models, based on the manufacturing process and a stage of the manufacturing process associated with an interconnection of the in-line instrument with the manufacturing process, to generate a prediction for the CQA based on data collected from the in-line instrument;
• collect, based on the one or more parameters, the measurement data in real-time from the in-line instrument;
• process the measurement data from the in-line instrument to generate real-time transformed data for the CQA and to predict a model output, the model output comprising trending data for the CQA;
• and
• store the trending data in a data storage device.

A method to establish monitoring for a Critical Quality Attribute (CQA) in real-time for an in-line instrument of a manufacturing process comprising:

• establishing one or more parameters for collecting measurement data from the in-line instrument, wherein the measurement data comprises an array of raw data per measurement;
• selecting a machine learning model for the in-line instrument from a library of machine learning models, based on the manufacturing process and a stage of the manufacturing process associated with an interconnection of the in-line instrument with the manufacturing process, to generate a prediction for the CQA based on data collected from the in-line instrument;
• collecting, based on the one or more parameters, the measurement data in real-time from the in-line instrument;
• processing the measurement data from the in-line instrument to generate real-time transformed data for the CQA and to predict a model output, the model output comprising trending data for the CQA;
• and
• storing the trending data in a data storage device.