Latest at Infometrix
Our three-day General Chemometrics Training Course is approaching soon. If you haven't already done so, sign up now
to reserve a spot. Also, a reminder that the dates for the course have changed from October 5-7 to October 19-21, 2016.
2016 Excellence in Analytical Technical Innovation Award
will be presented to Brian Rohrback, President of Infometrix, Inc. at the Fall Leaders' Meeting of the Instrument Society of America. Brian received an award from ISA's (Instrument Society of America) Analytical Division in recognition of what LineUp™
can do to improve the routine use of chromatography, particularly in process control and quality assurance settings.
The Importance of Data Exploration!
Some analysts who have been performing routine analysis for years tend to skip over a critical step in data analysis: data exploration. At Infometrix’ semi-annual training course, we spend 1/3 of the time discussing how to do data exploration, including visualization of data, cluster analysis, principal components analysis, and other techniques. We advocate that every dataset requires at least some amount of data exploration to ensure that the data being used is appropriate for the task. From the analyst’s perspective, this is how you:
- identify outliers before building a model
- reveal clustering of data
- flag potential process upsets
- understand any time, operator, or plant biases, or variations arising from other causes
Over time, an analyst can see similar patterns for so long that they skip straight to building a model or producing results without taking time to truly investigate each dataset from scratch. Whenever Infometrix joins a project, it is usually this initial data exploration phase that yields important observations, identifies issues that our clients have missed, and determines our approach for modeling. Our lack of familiarity in a project becomes an advantage when an analyst is not actively performing data exploration!
After Further Review...
Over the years, I have been involved in a lot of discussions tied to chemometric algorithms and their usefulness for all sorts of applications. In the early days (dating into the 1980s for me), the focus was always on chemometrics as a set of tools and the emphasis was on balancing the migrating platform variants (both computer and instrument software), training scientists to use the tools appropriately, and proving the value of the techniques in the application space. Now, well into our 4th
decade of software development, training, and servicing applications, a new balancing act is upon us. Although Infometrix will never ignore the software tools that represent the technical core of our business, we do find that many of the problems to which the chemometrics tools are applied (and are meant to solve) too often are shown to be effective but still languish in an R&D environment without ever seeing action as part of a quality control environment (where there is money to be made).
For chemometrics to play to its potential in manufacturing and production settings, we must focus on its role as a part (sometimes a small part) of the system as a whole. It takes a systems engineering approach; if we relegate the chemometrics to an isolated task status, deployment of an optimized system and its associated advantages are much less likely to happen.
So, it is not like building a wall. The better analogy is a Mandelbrot: a fractal pattern that is complex, asymmetrical and allows you to dive in as deep as you want to go to find the optimal view of your process. The chemometrics segment needs to tie in, sometimes in several different places, and it has to play nice with other system components causing us to consider not just the instrument source but also the database and control components. Getting the right pieces of data-derived information to the right place at the right time and in the right form (think dashboards and visualizations) is significantly easier given the advances in other areas of technology. Let’s do it.
Brian G. Rohrback
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