What is a soft sensor used for?
A soft sensor is used for the real-time prediction of a hard-to-measure variable, typically a product quality attribute.
Soft Sensors
Soft sensor implementation services for pharmaceutical manufacturers. The engagement covers the inferential measurement design, the data preparation, the model development, the model deployment, the integration with the DCS, and the validation.
Inferential measurement
The inferential measurement (soft sensor) is a model that predicts a hard-to-measure process variable from the easy-to-measure process variables.
Model development
The soft sensor model development covers the data collection, the data cleaning, the feature engineering, the model selection, the training, the validation, the testing, and the documentation.
Integration with DCS
The soft sensor is integrated with the DCS for the real-time inference, the display, the alarm, and the control.
How to use this page
Use this Soft Sensors page as a planning checkpoint before vendor selection, architecture review, validation scoping or implementation sequencing. The strongest next step is to compare the guidance with your current SOPs, system inventory, batch records, data flows and QA review routines so the discussion starts from evidence instead of assumptions.
Evidence to prepare
For Soft Sensors, prepare the records, owners, risks and decision criteria linked to inferential measurement, model development, integration with dcs. Useful evidence includes current process maps, interface lists, audit trail expectations, exception workflows, data retention rules and the business reason for changing the current operating model.
Frequently asked questions
How is the soft sensor validated?
The soft sensor is validated per the GAMP 5 framework for AI/ML systems.