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CAMO Software - Multivariate Data Analysis Software and Solutions

Advanced analytics

Advanced analytics are helping chemical manufacturers reduce process failures and improve yields and quality. With the need to reduce costs and improve product safety and sustainability, powerful tools traditionally used by analytical groups are being transferred to the plant floor.

Multivariate data analysis (MVA) is the investigation of many variables simultaneously, to understand the relationships that may exist between them. Multivariate data analysis methods have been around since the 1960s, but until recently were primarily used in laboratories and technical groups, rarely being applied to production processes.

Today, this is changing as manufacturers realise that the masses of data collected during production operations offer great insights to enable improved product development and process performance.

Because chemical manufacturing processes are typically highly multivariate in nature - i.e. a large number of variables which are usually interactive - they require multiple measurements to fully understand them.

Yet most statistical process control (SPC) systems rely on univariate methods, which only look at single variables, one at a time. Univariate statistics tend to fail when analysing complex systems because they cannot detect relationships between the variables, often the cause of process upsets.

Multivariate analysis tools allow engineers and production managers to better understand process behaviour and implement more robust control strategies. This enables them to:

  • run processes closer to limits
  • use lower cost components
  • reduce energy use
  • reduce cycle time
  • minimise waste

CAMO's solutions allow multivariate models to be developed by technical service groups or CAMO's consultants, and then applied to real-time production processes. The solutions can be used standalone to analyse off-line data, connected to databases or scientific instruments (e.g. spectrometers) or integrated with control systems for use by process operators.

Benefits for manufacturers

Manufacturers who have adopted these tools can quickly see improvements in their operations and on their bottom line.

Increased yields: Identify which combination of process variables produces the highest yield, and improve process understanding generally to find the optimum settings.

Improved quality: Root causes of quality problems can often be difficult to identify. Multivariate analysis gives deeper insights and can pinpoint the variables or their interactions causing problems. When combined with spectroscopy, it can enable cost-effective 100% quality testing.

Improved product safety and sustainability: Reduce the use of hazardous chemicals, minimise scrap and optimise processes for more sustainable products.

Reduced process failures: Identify issues in a process before they become problems causing the process to fail, and use powerful multivariate diagnostics to drill-down into the cause of the problem.

Reduced variability: Maintain consistent end-product quality more effectively by early correction of drifts in process using multivariate predictive models.

Cheaper product development: Experimental design lets you develop products faster and more cost-effectively, by reducing the amount of tests and experiments needed, as well as less use of destructive testing by replacing with spectroscopy.

Faster time to market: Move products from the pilot plant to full production scale faster. Multivariate analysis provides the product and process insights needed to help make scale up smoother to get to market faster.

About CAMO Software

CAMO Software specialises in multivariate data analysis software and solutions. Established in Oslo in 1984 and with offices in the US, Japan, Australia and India, CAMO are the makers of The Unscrambler® X suite of products, used by chemical manufacturers worldwide.

Our products and services

The Unscrambler® X

Leading multivariate analysis software used by thousands of engineers, data analysts around the world every day. It includes powerful regression, classification and exploratory data analysis tools, plus an integrated design of experiments module.

Process pulse

Real-time process monitoring software that lets you predict, identify and correct deviations in a process, before they become problems. It enables multivariate models to be applied to on-line, at-line and in-line processes. Affordable, easy to set up and use.

Hierarchical model development module

Software plug-in for the Unscrambler® X, offering a powerful decision-tree approach to multivariate modelling of complex data. Lets you join classification and prediction models, saving time and making modelling of non-linear data more efficient.

Prediction engine and classification engine

Software integrated directly into analytical or scientific instruments for real-time predictions and classifications directly from spectrometers using multivariate models.

Enterprise solutions

Apply powerful multivariate models across your R&D, production or QA/QC operations. Our customisable solutions can be integrated with instruments, process equipment and control systems to suit your needs.

Consultancy and data analysis services

Do you have a lot of data and information but don't have resources in house or time to analyse it? Our consultants offer world-leading data analysis combined with hands-on industry expertise.

Training

Our experienced, professional trainers can help your team use multivariate analysis to get more value from your data. Classroom, online or tailored in-house training courses from beginner to expert levels are available.

Contact Details


Europe, South and Central America, Mexico and South Africa
CAMO Software AS
Nedre Vollgate 8
Oslo
N-0158
Norway
Tel: +47 223 963 00
Fax: +47 223 963 22
Email: sales@camo.com
URL: CAMO Software Corporate Video
URL: Introduction to Multivariate Data Analysis
URL: Process Pulse
URL: www.camo.com

Multivariate data analysis (MVA) gives deeper insights into products and complex processes.
MVA identifies patterns and trends in complex data that statistical process control (SPC) tools cannot.
Chemical manufacturing processes are highly multivariate in nature, with many variables interacting.
Models can be developed by technical service groups or CAMO's consultants for use with control systems.
MVA enables engineers to understand process behaviour better and build more robust predictive models.
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