The Unscrambler®: Comprehensive Multivariate Analysis and Experimental Software

Regression, Prediction, Classification, Exploratory Analysis, DoE

Manufacturers in all industrial sectors continuously face major challenges regarding the improvement of product quality and in the early detection of process deviations. Multivariate Data Analysis (MVA) is well suited for designing quality into processes and provides the essential tools for monitoring Critical to Quality (CTQ) attributes, ensuring acceptable end product quality.

Generates models for better product and process understanding. Generates models for on-line prediction and classification.	Collect data directly from various software / instrument(s).
Eliminate unnecessary measurements & maximize ROI.	Define what is critical to quality & measure it. Early detection of process deviations through implementation of Multivariate Statistical Process Control (MSPC).

The Unscrambler® is a complete Multivariate Analysis and Experimental Design software solution, equipped with powerful methods including PCA, Multivariate Curve Resolution (MCR), PLS Regression, 3-Way PLS Regression, Clustering (K-Means), SIMCA and PLSDA Classification etc.

English


Descriptive Statistics ( Mean, Standard Deviation, Box-Plot, Skewness, Kurtosis, Cross - Correlation (Matrix Plot), Histo gram, Probability Plot) Principal Component Analysis (PCA), PCA Projection Multivariate Curve Resolution (MCR) Message list of recommendations in MCR modeling Clustering (K-Means) Classification (SIMCA, PLS-DA) ANOVA and Response Surface ANOVA Variable scaling options: Scaling is free on each variable. Suggested options: Auto-scaling, Constant, Passify Interaction and Square terms can be included in PCA, MLR, PCR and PLS-R models Varimax Rotation	Automatic detection of significant X-variables in PCR, PLS-R and PCA (Marten’s Uncertainty Test on Cross Validation, Stability Plots) Automatic outlier detection in PCA, MLR, PCR, PLS-R and Prediction Regression (MLR, PCR, PLS-R, 3-way PLS-R) MLR Prediction Prediction with Y-values and deviations (= uncertainty limits) Interactive analysis: - Mark samples and/or variables on plots - Recalculate with or without marked samples or variables - Recalculate with passified marked or unmarked variables - Extract data from marked or unmarked Automatic Pretreatments in Prediction and Classification Prediction from PCR, PLS-R and 3-way PLSR models	Design Wizard: Takes you through the stages of building a design Factorial(F) and Fractional Factorial (FF) designs Plackett - Burman (PB) designs Central Composite Designs (CCD) Box Behnken (BB) designs Mixture designs (Simplex- Lattice, Axial, Simplex-Centroid) D-Optimal designs of mixtures and non-mixtures Plots of main and interaction effects; Response Surface Modeling (RSM) Third order variable interactions	Smoothing: Moving Average, Savitzky Golay, Median filter, Gaussian filter Normalize: Area, Unit Vector, Mean, Maximum, Range, Peak Spectroscopic conversions: absorbance / reflectance, reflectance / Kubelka-Munk, wave number / nanometers Multiplicative Signal Correction (MSC) & Extended MSC (EMSC) Noise Insertion Derivatives: Norris-Gap, Gap-Segment and Savitzky Golay Baseline offset and Linear Baseline correction Standard Normal Variate (SNV) Mean centering, standard deviation scaling User-Defined Transformations (UDT), programmed for e.g. in Matlab or C++ and utilized in The Unscrambler® as a DLL Easy registration of pretreatment steps De-trending (1st to 4th polynomial order)

Combines ease-of- use with comprehensive DoE and MVA methods
Ensures greater ROI by reducing the number of experiments required
Generates models that can be used for on-line prediction and classification in CAMO Software's Online Unscrambler Predictor (OLUP) & Online Unscrambler Classifier (OLUC)
Generates models that can be used for faster product and process optimization in CAMO Software's Unscrambler Optimizer

Pharmaceutical & Biotechnology

Improved understanding of drug manufacturing processes. Provides data analysis tools for implementing Process Analytical Technologies(PAT) & Quality by Design (QbD) initiatives
Creation of classification and prediction models that can be used with third party software and Instrumentation. Applications include, raw material identification and quantification of active drug ingredients
Analysis of data, isolating those process variables that impact on drug product quality

Chemical

Allows the implementation of MSPC in conjunction with the Unscrambler Online

Food & Beverage

Efficiently formulate new products & determine their consumer preference attributes

Energy

Facilitates fuel classification according to type and correlates physical parameters such as Density, Flash Point, Naphthalene’s, Aromatics etc
Enables determining of the proportion of Carbon Monoxide, Nitric Oxide and water vapor concentrations for different engine conditions and at different temperatures