Maximize Data Analysis with METTLER TOLEDO FBRM®

METTLER TOLEDO FBRM® provides an information-rich method for tracking the number and dimension of particles or droplets as they actually exist in process. In any given particle system, there are specific and possibly unique, changes that are of critical importance to the user. This three part complimentary webinar series will provide you with the knowledge, information and best practices you need to maximize your data analysis.

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Maximize Advanced Data Analysis with FBRM Webinar Series

Columbia, MD (PRWEB) January 22, 2009

METTLER TOLEDO invites you to attend a three part complimentary webinar series - Maximize Data Analysis with METTLER TOLEDO FBRM® - presented by Eric Dycus, Particle System Characterization Technology and Application Consultant, beginning on January 27, 2009.

Part I - Mechanisms of Particle Change - Tuesday, January 27
How does FBRM® track particle agglomeration, breakage, attrition, nucleation, growth, and shape? How can users extract a mechanistic understanding of these changes from FBRM® data? Part I will provide examples of particle size distribution changes as characterized by FBRM® and PVM®. Example of particle agglomeration, growth, breakage, and shape change will be presented providing you with a foundation on how various particle changes manifest in the data. By using the correct analysis tools, weighing, and statistics, specific particle changes can be understood and optimized with maximum precision.

Part II - Correlating FBRM® Directly to Process Efficiency and Product Quality - Tuesday, February 10
How can FBRM® be correlated to predict downstream process efficiency or product quality? How can FBRM® be correlated to an offline particle measurement such as laser diffraction, sieving, or microscopy? Part II will provide examples of direct correlations between:
FBRM® data and process efficiency such as filtration, flow properties, or dissolution rates; FBRM® data and product quality such as bulk density, stability, color, and particle size; FBRM® data and offline laser diffraction, the sieve, and image analysis; Caveats to correlation as well as successful correlations and case studies will be discussed.

Part III - Overcoming Pitfalls to FBRM® Data Interpretation - Wednesday, February 25
How do changes in particle system physics affect FBRM® data? The FBRM® measurement principle has inherent sensitivity which can affect results in ways expected by chemists and engineers. Understanding these particle system properties can significantly increase success with FBRM® data interpretation. Part III will discuss specific case studies to maximize data analysis with particles undergoing the following changes: concentration, dilution, segregation, index of refraction, smoothness, brightness, flotation, settling.

At the end of each webinar, there will be an interactive question and answer session providing you with the opportunity to ask questions relevant to your particular application.