Umetrics Announces Release of SIMCA® 14 MVDA Software

Python® Scripting, Workspace, What If Predictions and New Visualization Plots

Malmö, Sweden, January 28, 2015 - Umetrics announces the release of version 14 of SIMCA®, the standard in multivariate data analysis.

Umetrics is known for helping engineers, analysts and scientists to master their data using SIMCA® software. Whether it is batch data, time-series data or any other kind of data, SIMCA® transforms raw numbers into graphical information for easy interpretation, enabling decision making to take action - quickly and with confidence. Now, SIMCA® 14 introduces these additional enhancements:

  • Scripting using Python® - Write and use scripts to automate your day-to-day work.
  • "What-If" Analysis - The ability to predict what will happen when data is adjusted, making SIMCA® 14 an excellent tool for simulation and process understanding.
  • Workspace Ease of Use Enhancements - All plots, customized as desired, are saved and reopened the next time you open the project. Facilitates sharing information across your organization.
  • Batch-OPLS - Batch models for batch evolution can now be based on OPLS allowing superior interpretation.
  • New Graphics and Plots - SIMCA® 14 offers the outstanding graphics and visualization tools for multivariate data analysis, now including the new plot ROC and plot type DOT.
  • Models built in SIMCA® can be used in Umetrics SIMCA® product suite including SIMCA®-Q 14 and SIMCA®-online 14.

For more information:

Visit the Umetrics SIMCA® web site

About Umetrics
Umetrics is a world leader in multivariate technology, providing software for design of experiments (DOE) and multivariate data analysis (MVDA). Umetrics offers complete solutions for both off-line and on-line data analysis (continuous and batch processes), all supported by training and consulting services. Umetrics is a subsidiary of MKS Instruments, Inc. (NASDAQ: MKSI), global provider of instruments, subsystems, software and process control solutions to manage critical parameters of advanced manufacturing processes. More information can be found at Umetrics website