SIMCA 17

Download brochure SIMCA 17 .pdf
Why SIMCA .pdf

Explore. Analyze. Interpret

SIMCA enables you to effectively explore your data, analyze your product, process or system, and interpret the results, no matter how large or how many variables your big data may consist of. Its comprehensive plot library provides visualization that you won’t find elsewhere, making your task not only easier, but also more enjoyable.

Improve your understanding

The better you understand what’s really going on in your systems, the better prepared you are to make decisions that will reduce the risk of failure, improve product quality and lower costs. With the right tools for analyzing data, you can raise your product understanding dramatically, simplifying both product optimization and the development of new and better products and processes.

The foundation for successful PAT & QbD

Multivariate data analysis provided through SIMCA is a cornerstone in the implementation of Process Analytical Technology (PAT) and Quality by Design (QbD). Your data is complex, but SIMCA is exceptionally easy to use and lets you visualize what you really need to know. It has become a valuable for PAT and QbD solutions used in pharmaceutical and biopharmaceutical development and production.

Unique handling of batch process data

SIMCA provides huge greater flexibility for batch process modelling by enabling multiple data sets inside the same project. Process, lab and spectral data as well as any other available data can easily be collected, analyzed and modeled within one single file.

Handle multiple data sets in one project

SIMCA lets you work with several data sets in the same project, providing exceptional handling and modeling of multiple types of data arising from the same system.

Voor prijzen of offerte stuur ons een e-mail. For prices or offer please send us an email.

What is DOE? Design of Experiments Basics for Beginners

Click here for Umetrics SIMCA Sartorius website;
Click here for the Webinars Simca (the product for Process analytics)