Unscrambler X Process Pulse - 8 Pages

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Catalogue excerpts

Easy to use multivariate process monitoring solution for on-line or at-line applications ■ Predict and correct ■ Customizable, easy to ■ Affordable, flexible and process deviations before set up and easy to use for scalable for almost any they become problems > process operators > process environment > Bring data to life

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02 CAMO Unscrambler® X Process Pulse “ Process Pulse has proven to be versatile and configurable to suit our unique management system for monitoring and controlling our production processes. Process Pulse has been very useful for PAT (Process Analytical Technology) implementation in our manufacturing plant. “ Josep Ma. González, Director of Quality, Menarini Group, Spain Process Pulse can help organizations: Reduce process failures with Early Event Detection Improve yields through better process understanding Reduce variability and improve end product quality Reduce raw material, scrap, energy...

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Software for every industry Unscrambler® X Process Pulse can be applied across many industries and research fields to improve product development, manufacturing and quality control by near real-time monitoring of processes with powerful multivariate models. Pharmaceuticals & Biotech Research & Academia Chemicals & Petrochemicals Energy & Renewables Agriculture Automotive Food & Beverage Medical Devices Pulp & Paper Electronics Mining & Metals Engineering Oil & Gas Semi-conductors Manufacturing Aerospace & Defense Unscrambler® X Process Pulse 03 CAMO

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04 CAMO Unscrambler® X Process Pulse Process Pulse can be used for end-point modeling, with the plot above showing a pharmaceutical drying process monitored using NIR spectroscopy. The model is trained to identify when the process has reached its end state i.e. sufficiently dry. New batches can be monitored as they move toward the end point, shown by the area in the ellipse (top left ‘Scores’ plot). This enables users to make sure they don’t stop the process too early nor continue it longer than necessary. Process Pulse has extensive drill down options. The figure above shows parameters from an...

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Unscrambler® X Process Pulse 05 CAMO The figure above shows the predicted concentration of three different components in a pharmaceutical blending process. The upper right ‘Scores’ plot indicates that the overall product is within specification, with all data within the ellipse. Projection is a new feature in Process Pulse 1.1. Projection enables the user to apply a multivariate model to new samples to see how the new samples compare with the calibration data, even in cases where there are no responses to predict. Simultaneous use of multiple prediction models is a new feature in Process Pulse...

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06 CAMO Unscrambler® X Process Pulse During prediction and process monitoring, outlier statistics are powerful tools for identifying if samples differ to those used in the calibration set. Such outlier statistics are used for detecting process deviations, potential process upsets or measurement issues. Q-residuals (bottom right plot in figure to left) is another powerful outlier diagnostic in Process Pulse. It detects if completely new variations are observed in new samples compared to the calibration data. For example this may indicate if equipment failure is about to occur or if new constituents...

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Unscrambler® X Process Pulse < 07 CAMO Features of Process Pulse version 1.1 General Real Time Wide Range of Data Imports > Accepts ASCII and Excel formats > Supports most spectroscopic data formats ncluding JcampDx, Grams (*.spc), Bruker OPUS, Bnmrose (*.BFF4), ASD Indico, Omnic (*.spa), Vanan (*.bsw),Guided Wave, NSAS (Foss NIR Systems), Perkin Elmer (*.sp) > Plug n Play style setup > Uses The Unscrambler® X predictive anc classification models > Set up wizard guides user through the process > Simple product tree and data view formats Utilises full capabilities of The Unscrambler® X > Prediction...

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About CAMO Software Founded in 1984, CAMO Software is a leader in Multivariate Data Analysis and Design of Experiments solutions with offices in Norway, USA, Japan, India and Australia. Multivariate analysis is a powerful set of data mining techniques that help identify patterns and understand the relationships between variables in complex data, allowing organizations to: Efficiently analyze big data sets Build better predictive models Accelerate R&D timescales Efficiently scale up to production Reduce process cycle time Reduce process or equipment failures Reduce final product variability Improve...

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