Spectral Data (available December 2019)

This module offers multivariate statistical methods to turn spectral data into actionable knowledge.  Well-utilised spectral information will quickly become a valuable asset that enables visualisation of process variations, prediction of product quality and identification of critical process parameters.

Spectra from both offline and in-process instrumentation can be seamlessly cleaned and transformed using chemometric methodology, to develop fully traceable calibration models for real time applications.

Key features include:

• Selection of spectral range
• Pre-processing, including baseline adjustment, Normalisation, Savitzky-Golay Filtering
• Calibration Modelling using PLS regression and MVSC
• Visualisation through configurable graphical workflows
• Audit Summary Report