Predictive models for product, process

Process Modeler is a software tool for creating predictive models of product properties, production, and process events. Models are typically used as ‘virtual sensors,’ property predictors, and as a foundation for model-based closed-loop industrial process optimization.

The BioComp Systems tool reportedly cuts modeling effort by 70% and is said to be easy for any process- or product-engineer to use. Product also helps users identify and graphically visualize causes of product and process performance or problems through scatter plots, sensitivity analysis, ranked lists of key performance drivers, and 3-D response surfaces. It is said to enable users to predict product performance before lab results, predict properties that cannot be measured on-line, backup sensors with quality estimates, and estimate conditions in hostile environments.

Data can be graphically filtered to focus analysis on specific points in time. A built-in auto filter handles variables as needed, or users can create custom filters by dragging across data. Filter support includes keep/discard between upper and lower values, keep/discard between a start and stop record, or keep/discard within a box. Models can be validated before going on-line by viewing key performance drivers ranked by strength. Users can confirm that models meet accuracy criteria and will provide the expected response.

www.biocompsystems.com/products/processmodeler/index.htm

Virtual sensors/sensor validation

Property predictors

Process analytics and understanding

Model validation

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