The Multivariate World Is Expanding

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The Multivariate World Is Expanding

The field of chemometrics has been around for quite some time now and has played its role in both research and industrial environments. While the multivariate research toolbox is well established and ever increasing, its industrial counterpart is only beginning to see widespread use in the last decade. This could be due to many reasons such as the advancement of industrial data management solutions, the semi-continuous financial crises that drive the industry to smarter manufacturing and the use of data to reduce costs and waste. Whatever the reasons, it is clear that chemometrics and multivariate analysis have a big role to play in connecting the dots between research and the new paradigm with advanced and more robust sensors, agile manufacturing processes and product quality control. Welcome to the multivariate world!

We believe that all processes or systems are multivariate in nature until proven otherwise and therefore they must be analysed, modelled and understood as such! There are two important aspects in any field that requires experimentation; the ability to understand the outputs of the experiment and the ability to put this newfound knowledge to use for future situations. Whether the experiment involves spectral measurements, sensory data, manufacturing process data or psychometric variables, the two main outputs everyone is looking for are; can I understand the process/experiment and how can I put my findings to good use. All you need is the right multivariate tools to understand the data and to generate valid and robust models. Then you are ready to apply these models in real-world situations.

While multivariate methods lend themselves well to empirical analysis of data sampled from science, technology and nature (i.e. any system with multiple underlying structures) there is nothing that prevents the use of the first principle models in combination with actual observations.

CAMO’s philosophy is not to describe all methods in the world or to include them in our software, but to provide methods that are versatile and suited for any kind of data, regardless of their size and properties. CAMO believes that the focus should be on graphical presentation of results rather than tables with p-values. This is related to the distinction between significance and relevance. With a high number of objects any test for significance between two groups or correlation between two variables will be statistically significant. Thus, a table of p-values does not show if the model is suitable for predicting selected properties such as the product quality at the individual level.

When this is said we realise that summarising the important findings from a project or study is often efficiently done with bullet points or univariate statistics. Our message is that multivariate methods provide the fastest insight into complex data to arrive at the correct conclusions and to avoid “searching for correlations”.

The situation is that even after 40 years of multivariate methods and in particular multivariate calibration, it is not known to the majority of people that selectivity is not needed to predict quality of a product or classify or identify samples such as raw materials.

Finally, being a data analyst is about practicing the methods and software on your own data.

I wish you all the best, and may your models be with you!

frank-grey

 

 

 

 

Dr Frank Westad, Chief Scientific Officer, CAMO Software

 

Can Assumption-Free Batch Modeling Eliminate Processing Uncertainties?  

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With Industry 4.0 around the corner and concepts like continuous manufacturing, the future is almost here. But not quite yet. In the meantime batch processes will continue to be a common practice in manufacturing.

For the longest time we have found that the multivariate modeling of batch processes has been imprecise and even inaccurate. Hence, we have invested time and resources in coming up with a new way of modeling that can bring us closer to the true batch trajectory. This breakthrough brings many benefits to our customers and can be translated into real return on investments. Some examples to mention are detecting and adjusting out-of-spec situations and events early, and predicting product quality at an early stage to comply with regulatory requirements. Finally, understanding the process and making it more transparent will give the ability to develop the process further and improve the operational efficiency.

The interest for this new solution has been great, and emphasizes that it is a real problem that many are challenged by. For a long time we have had to settle for estimates without knowing what the total impact would be, and as long as it looks like we are within our limits we have to assume it is all good. This new methodology represents a starting point to achieve new levels in  production processes and also a positive  step towards the Industry 4.0 paradigm.

New article about Batch Modeling applications available on Pharmaceutical Online

Partners for life and for greater value to our customers

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CAMO Software recently hosted a Partner Conference for our European partners, where many engaging conversations took place over the course of the conference. One thing made clear was our joint quest on a mission to improve the experience for the end user, to reduce complexity and to add direct value to business critical units and operations. As much as I would like to believe that the world is full of data scientists that thrive on analysing data all day long, it is only a small portion of manufacturing companies or pharmaceutical supply chain players that do so. The reality is that we frequently get asked to provide plug-and-play solutions that customers directly can integrate in their infrastructure and they depend on us and our partners to provide expertise in multivariate analysis and chemometrics. I would go as far as saying that they expect us to provide not just the tool to analyse their data but also the means of putting our software to work.

The eco-system in the world of data analytics, and in particular the industrial usage of data analysis of processes, is where real customer value innovation will take place. We are driving on a road towards more open interfaces where it should be easy to combine hardware with software and connect data management systems with analytics capabilities. It is also a destination where customers are looking for greater value in the shape of training and consulting services, allowing the end users to focus on their core business while we offer the edge they need in an easily consumed package, to improve product quality, production efficiency and ultimately gain a competitive advantage in their respective market place.

There are many reasons why I think that our partners are a key asset not just for us, but also for the customers, who are looking for solutions to their specific requirements. The appetite for ready to use solutions is getting bigger and everyone is looking for means of bringing their data to life. As a result of the increasing demand for user friendly and easy to implement software that enable non data scientists to maneuver through the data analysis world, CAMO has introduced our multivariate process monitoring solution, Process Pulse II. This solution aims to fill the void between advanced analysis development and its application in a manufacturing environment. In this context it serves as a proof of the value we can add by reducing complexity and making a data scientists’ work applicable in a much wider spectrum of operations that will further enhance the value added to the end users. And that’s what both CAMO and our partners are set out to do – bring data to life for our customers to enjoy the benefits of multivariate analysis.

Are you interested in understanding more about our Process Pulse II?

Try Process Pulse II

Read more about Process Pulse II

Pittcon 2016 trends: Food safety, miniaturization of spectrometer technology, and software driven data collection

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John Richmond, the CAMO Business Development Director for the USA attended the 2016 Pittsburgh Conference, held in Atlanta at the Georgia World Congress Center, from March 5th to March 9th.   Pittcon is the world’s leading annual conference and exposition on laboratory science. Pittcon attracts more than 16,000 attendees from industry, academia and government from over 90 countries worldwide.  As CAMO Software is the leading provider of Multivariate Analysis software (MVA) with flagship products such as The Unscrambler® X and Process Pulse II, Pittcon is an important event for developing partner relationships and identifying new trends in the areas of both Laboratory and Process Analysis.  Many of the CAMO partners were exhibiting such as Viavi Solutions with their new MicroNIR spectrometers, MicroNIR PAT and MicroNIR OnSite.  The trend for miniaturization of spectrometer technology was evident with many other companies following in the wake of Viavi Solutions.  In the benchtop spectrometer area, amongst the new companies’ present was Galaxy Scientific (Nashua, NH) with their range of Fourier Transform Near Infrared spectrometers – the QuasIR series.

On the applications side, the conference highlights were food safety and the emerging opportunities in the legal cannabis market, which is projected to be a $10B market by 2018. Companies such as Sage Analytics are well positioned to take advantage of this with their recently released Luminary spectrometer series.  As the demand for the technology grows, stable, reliable, robust multivariate analysis methods, developed under the same regulatory requirements as the pharmaceutical industry, will be needed for the analysis of both major and minor components.

Software driven data collection and analysis along with new technology development promises a vibrant and exciting future for vendors and customers alike. With an annual data growth rate of 40% (source: IDC) the reality is that we have more data than ever to analyse and put into parctice to achieve long desired benefits to improve quality of products and efficiency of processes all together.

Take a look at http://pittcon.org/ to see more about the conference.

The NEW Unscrambler® X Multivariate Data Analysis and Design of Experiments software

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The Unscrambler® X 10.4 continues CAMO´s tradition of delivering advanced multivariate data analysis software that is easy to use and offerings exceptional data visualization. It includes exploratory data analysis, regression and classification methods, predictive modeling, design of experiments and descriptive statistics. The Unscrambler® X is used by engineers, scientists, researchers and data analysts across R&D, QC and Production departments in a wide range of industrial sectors from life sciences to chemicals and food production as well as academia and research.

One of the main new features of version 10.4 is the replacement of the former Design of Experiments (DOE) module with Design-Expert® from Stat-Ease. Design-Expert® is the most complete and world-leading DOE software on the market, and provides a wide range of new designs and analysis tools. The new version of The Unscrambler® X is integrated with Stat-Ease’s new version of Design-Expert® version 10.

Furthermore, the new version offers several new methods, such as Moving Block Methods and Statistical Process Control for trending of process data, Piecewise Direct Standardization for calibration transfer, improved plotting tools, a number of changes to PCA/PCR/PLSR analysis dialogues and more flexible usage of outlier statistics.

Shirley A. Henshall, CEO of CAMO Software, says, “This Unscrambler® release provides a major advancement, as it is the first version that fully demonstrates the power of the collaboration between CAMO Software and Stat-Ease®. By combining the domain expertise from these two leading companies we are truly enhancing the offering to our customers and providing a comprehensive package for both Multivariate Analysis and Design of Experiments”.

Other key features included in version 10.4 are Sample Alignment for merging two or more data tables based on sample time stamps or category levels, and import from Design-Expert®, and many other data sources.

  • Current users of The Unscrambler® X are encouraged to upgrade to the new version.
  • A free 30-day trial version of The Unscrambler® X 10.4 is available for download from www.camo.com.

Pressrelease

 

CAMO Software partners with key reseller in Puerto Rico

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CAMO Software Inc. (Woodbridge New Jersey) are pleased to announce that they have appointed IBS-Caribe as their reseller in Puerto Rico. As well as selling CAMO Software’s state-of-the-art software products such as The Unscrambler® X and Unscrambler® X Process Pulse II, IBS-Caribe will also offer technical support, training seminars and workshops to existing and prospective customers. John Richmond, USA Business Development Director for CAMO Software Inc. states “Puerto-Rico is an important market for CAMO particularly due to the pharmaceutical manufacturing sector. This strategic partnership with IBS-Caribe is part of CAMO’s efforts to offer our products and services on a much wider basis than before and we are excited to work with the local experts in the field”. Manuel Hormaza, President of IBS-Caribe states “CAMO’s software products fit perfectly with our vision of to establish process understanding by connecting analyzers and sensors at the shop floor, in real-time. CAMO’s software is innovative, easy to use and is well accepted by customers in Puerto-Rico”.

About IBS-Caribe
IBS Caribe, Inc. is a growth oriented company, founded in 2004, to provide innovative solutions to the regulated Life-Sciences manufacturing industries in Puerto Rico and the Caribbean. IBS main customers are Life-Science manufacturing companies that introduce innovative process monitoring and control systems, such as vibrational spectroscopy analyzers and automation systems. IBS has developed partnership agreements with selected major suppliers to promote, sell and service PAT Products in Puerto Rico and extended Latin America. IBS provides a project lifecycle approach which includes applications support, feasibility studies, IQ/OQ and Maintenance.

Product Release: The Unscrambler® X Design-Expert® Upgrade

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The Unscrambler® X Design-Expert® Upgrade

CAMO Software and Stat-Ease are pleased to announce the release of a new product bundle; The Unscrambler® X Design-Expert® Upgrade.

This bundle combines CAMO’s leading software for multivariate data analysis, The Unscrambler® X and Stat-Ease’s acclaimed software for design of experiments, Design-Expert®.

The Unscrambler® X offers advanced multivariate methods, data visualization tools and the ability to cut through large data sets. It is used in the pharmaceutical, food & beverage, chemical, energy, mining & metals, paper and agriculture sectors.

Design-Expert® enables users to make breakthrough improvements to a product or a process. One can not only screen for vital factors, but also locate ideal process settings for top performance and discover optimal product formulations.

Together, the product bundle will provide customers with access to two world-leading software packages providing advanced data analysis in one solution.

Read more about The Unscrambler® X Design-Expert® Upgrade here.

CAMO will together with Stat-Ease arrange a training course in Oslo, Norway in November, and you can already sign up here.

Our friends in the US can sign up for Stat-Ease training courses in September and November, read more here.

Product Training: Experiment Design Made Easy (EDME)

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Date: November 04-05, 2015 | Oslo, Norway

Find out how to make breakthrough improvements using powerful design of experiments (DOE) techniques. Start with our Experiment Design Made Easy workshop to learn about using factorial designs for finding which factors you need to focus on. Discover previously unknown interactions that often prove to be the key to success. Learn how to use powerful ANOVA analysis methods that give you confidence in your findings.

Experiment Design Made Easy covers the practical aspects of DOE. (Students may purchase the optional “DOE Simplified” book for reference.) You learn all about simple but powerful two-level factorial designs. During this introductory DOE workshop, you will discover how to effectively:

  • Understand the motivation for factorial designs
  • Implement the DOE planning process
  • Interpret analysis of variance (ANOVA)
  • Discover hidden interactions
  • Capitalize on efficient fractional designs for screening or characterization
  • Use power to properly size designs
  • Determine when to use transformations
  • Explore multilevel categoric factors
  • Set up split-plot designs
  • Follow the strategy of experimentation from screening to response surface methods

Click here for details.

Sign Up

 

 

Product Release: Unscrambler® X Process Pulse II

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Unscrambler® X Process Pulse IIWe are pleased to announce the release of a new version of our easy-to-use multivariate process monitoring solution, the Unscrambler® X Process Pulse II.

The new version provides users with many new and improved features, including parallel import and alignments of multiple data sources in real time, running and visualization of models with real time flagging of deviations, as well as data historian for simplified troubleshooting. The new version has also been updated with a new and more intuitive user interface.

Unscrambler® X Process Pulse II is used in a wide range of industries and research fields, for improvement in product development, manufacturing and quality control. Using powerful multivariate models, the software helps manufacturers and process operators identify and correct deviations before they become problems. The product includes predictions, classifications and projections, presented in an intuitive graphical interface, and is easily integrated with third-party production and processing systems.

Key business benefits that can be achieved from using Unscrambler® X Process Pulse II include:

  • Reduce process failures with Early Event Detection
  • Improve yields through better process understanding
  • Reduce raw material, scrap, energy and rework costs
  • Speed up cycle time and run processes closer to limits
  • Accelerate scale up from R&D to production scale

To learn more about Unscrambler® X Process Pulse II and watch in action, please take a look at the webinar recording here.

In the coming months we will also arrange training courses for Unscrambler® X Process Pulse II, please watch our training section for updates.

Take a look at our new Unscrambler® X Process Pulse II introduction video!

Tech Tip: Combining Data Matrices

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Often, during the initial setup of a project (or when revisiting one), there is a need to combine data matrices. It may be that new data has been collected that needs to be added to a calibration set. Or perhaps you are combining data sources for the same samples (process data, spectroscopic data, analytical tests, etc). In simple cases, you can always copy/paste the desired information, but if you have more than 2-3 matrices to combine, this can be a hassle. A nice, quick alternative is to use the Matrix Calculator function in The Unscrambler® X. This example will show combining sample sets.

1) Import all the data that you are interested in combining, and label your data matrices appropriately.
2) Check that number of variables/samples is consistent with each matrix. If appending new samples, then the number of variables must be the same and in the same order. If augmenting new data for existing samples, then the number of samples must be the same and in the same order. Note stay tuned for our upcoming sample alignment tool!
3) Select Tools – Matrix Calculator
4) Check the boxes next to each of the matrices you want to combine. And click on the Shaping tab.
Optionally, you may select Add category variable, which will add a new column with a category variable labeling which matrix the data came from. This is especially helpful when combining batches or different raw material types (such as in this example).
5) Click on Append to combine the data sample-wise. Note: clicking on Augment would combine the data variable-wise. Notice it is not currently available because the matrices do not have the same number of samples.
6) Click Close, and check your new combined matrix. If you clicked Add category variable, you will see that appended to the end of the matrix.

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