INSTEP Automated Chemometrics Prediction Software

Complex applications benefit from the increased prediction accuracy and sensitivity to outliers (e.g., unusual samples, process upsets) associated with a multivariate approach. Generating a decision tree around a classification model (predicting a sample category), a regression model (predicting a continuous property or concentration), or any combination of both model types allows predefined rules to be applied to complex problems. When coupled to a given instrument system, the result is a turn-key custom analyzer.

Complex applications benefit from the increased prediction accuracy and sensitivity to outliers (e.g., unusual samples, process upsets) associated with a multivariate approach. Generating a decision tree around a classification model (predicting a sample category), a regression model (predicting a continuous property or concentration), or any combination of both model types allows predefined rules to be applied to complex problems. When coupled to a given instrument system, the result is a turn-key custom analyzer.

The key aspects of InStep are:

  • its behind the scene use of Pirouette to make predictions
  • a form-based interface for creating decision trees using multivariate models
  • a “watched folder” approach which allows it to run concurrently with instrument data acquisition programs
  • generation of custom reports which can be displayed on-screen and/or saved to a file
  • presentation of control charts for visual monitoring of results and diagnostics

InStep Features:

  • Easy setup of InStep prediction methods
  • Complex heirarchical methods are possible with InStep
  • Specify location for files to be processed
  • Create a report format for the predictions
  • Customize the output with meaningful commentary
phase

Gas, Liquids, Solids

industries

Automotive, Bio Energy, Chemical, Environmental & water treatment, Fermentations, Food & Beverages, Petrochemical, Pharmaceutical & Bio Pharma, Polymers, Power Plants, Semi-Conductor, Steel Plants, Sterilization