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By in-house training, our courses become even more valuable. There's the obvious, positive synergetic effect in a whole group of colleagues being trained at the same time, but also the openness for in-depth discussions on the specifics of your own application areas. Please review the list of available courses and seminars below. Click on the course title for detailed description. To discuss a convenient date, or a course for a specific application, please contact us.
Basic courses
All courses are three days long and assume no prior training in statistics.
Advanced courses
All courses are one day long and assume prior training or experience in relevant method. A combination of advanced courses with a one-day refresh of the basic course is available on demand.
Half-day Seminars
We offer four-hour seminars to introduce the benefits and basic principles of multivariate technology.
MVA Metab Europe
Multivariate Analysis for Metabolomics
Multivariate data analysis is essential in the process of distilling information from the complex data sets involved in Metabolomics. Discover how to build valid and predictive models based on data from in vivo metabolic profiles, with the latest multivariate techniques.
The course is composed of lectures, demonstrations and computer exercises using SIMCA-P+ software on real-life datasets.
After completing the course, participants will know how to:
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Apply PCA to detect outliers, trends and patterns in metabolomic data |
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Use SIMCA classification techniques for identification of treatment groups |
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Interpret models to gain scientific insights |
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Use PLS-DA for identification of potential biomarkers |
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Construct predictive models and apply them in practice |
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Validate models for robustness and predictability |
Who should participate?
The course is intended for researchers involved in both MS- and NMR-based metabolomics. No prior knowledge of statistics is assumed. Some familiarity with mass spectrometry and NMR spcetroscopy is required.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction to multivariate data analysis – the three main problem types. Geometric representation of multivariate data. Problems with classical approaches. Principal Component Analysis (PCA) to overview data tables. SIMCA Classification of metabolomic data. Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Partial Least Squares (PLS) regression: finding connections between multivariate X and Y. Geometric representation of PLS. Evaluating PLS models: PLS-Discriminant Analysis. Metabolomic data handling. Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Batch modelling; comparison of individuals with treatment time courses. Advanced data filtering and signal correction techniques. Computer exercises followed by discussion. Analysis of delegates’ own data. Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
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DOE Pharma Windsor
Design of Experiments, Pharmaceutical Applications
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability. The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE. Examples and datasets originate from applications within the pharmaceutical industry and other related industries.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimize products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimise. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
This is a basic Design of Experiments course, intended for researchers, scientists and engineers within life science industry. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:30 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:30 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 16:00 |
End of course. |
Cost and conditions
The course fee (+VAT) includes lunch each day and the course dinner on Tuesday evening. The course will be held at our offices in Winkfield. B&B accommodation is available at the nearby Harte & Garter hotel in Windsor at preferential rates. Umetrics will organise accommodation at the hotel but delegates are responsible for settling their own bills. Cancellations received later than two weeks before the course starts will be charged at the full rate. Providing that Umetrics is notified, the registering company may substitute participants.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
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US_PAT
Umetrics is pleased to offer a training course in process analytical technology (PAT). This three-day course is dedicated to the multivariate methods and applications essential for development of process understanding and execution of PAT projects. The topics covered include analysis of raw material variation, MV calibration, batch analysis and design of experiments. Applications include MV calibration, end point detection, multivariate monitoring (real-time MSPC) of batch processes, identification of critical process parameters, prediction of quality and a methodology for modeling complete production trains. There is also discussion of data infrastructure requirements that enable these types of analysis.
After completing this course the participants will:
- identify critical process parameters
- evaluate manufacturing performance for quality investigations
- understand the technology required to accomplish PAT objectives
- quantify the influence of raw material and process variation on product quality
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MVA Method Extensions s-in
Advanced Multivariate Method Extensions
This two-day advanced course is dedicated to the multivariate approach of how to handle spectroscopy data. It begins with a refresh of the basic methods, followed by new applications and new developments in theory. The advanced course is by far the best way to keep updated on what's hot and what's not.
The course will include both tutorial lectures and practical exercises in software SIMCA-P+ using well-established material from Umetrics AB. Additionally, course participants will be given the opportunity to work with their own data and to discuss analytical matters with the tutors.
After completing the course, participants will know how to:
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Be able to attack problems with new and refreshed skills in analysis |
| • |
Have a deeper theoretical understanding |
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Have discussed and exercised new areas of applications |
Who should participate?
The advanced course is intended for those who have attended the multivariate analysis basic course, or have equivalent training or experience Knowledge in SIMCA-P is preferable.
Course schedule
Lunch daily between 12:30 - 13:30 |
| Day one |
| 09:00 |
Course start.
Review of PCA, Exercises.
Review of PLS, Exercises.
Advanced methods for centering and scaling.
Demo in SIMCA-P+.
Discussion of exercises and applications. |
| 17:00 |
End of lectures and exercises.
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| Day two |
| 09:00 |
Review of day one.
The calibration model building process.
Six main steps of multivariate calibration.
Design of experiments and sampling in multivariate calibration for robust model building.
Signal correction and compression.
OSC, OPLS, PLS-DA.
Computer exercises and discussions. |
| 17:00 |
End of course. |
Cost and conditions
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than 2 weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s) freely, if desired. The course will be held at S-IN Soluzioni Informatiche, via Ferrari 14, 36100 Vicenza.
To register, please use the button "Begin registration" in this window frame, or send an email to training@s-in.it.
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MVA PAT Windsor
Multivariate Analysis for PAT
Process Analytical Technology (PAT) is a drive within pharmaceutical manufacturing to improve process understanding, process consistency and provide a framework for continuous improvement. This course enables understanding of the central role of multivariate analysis in this process. Delegates will learn how to interpret complex data quickly and confidently, and find out how to build robust predictive models that turn data into decisions.
The course is composed of lectures, demonstrations and computer exercises in software SIMCA-P+, based on real-life datasets.
After completing the course, participants will know how to:
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Apply PCA (Principal Component Analysis) to detect outliers, trends, patterns and to classify groups within complex data |
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Relate multiple responses to multiple inputs using PLS (Partial Least Squares) modelling |
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Interpret models to gain scientific insights |
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Learn how to model processes and use multivariate calibration to improve quality |
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Characterise raw materials and ingredients |
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Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers in life science industry, or with an interest in PAT. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction and presentation of three kinds of problem: overview, classification, and quantification and prediction.
Principal Component Analysis (PCA) for overview of data tables: variable scaling, geometrical interpretation, and model evaluation.
PCA examples: quality control of manufacturing, process control (SPC) and environmental monitoring.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. Dinner in Cork.
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| Day two |
| 09:00 |
Partial Least Squares (PLS): prediction of responses Y from inputs X e.g. spectra, process variables etc.
Variable scaling, geometrical interpretation, algebraic solution and model evaluation.
Multivariate characterisation: quantification of qualitative differences (batches of raw material, chemicals, suppliers).
Multivariate calibration: prediction of chemical contents from spectroscopic data.
PLS examples: NIR calibration of API concentration in tablets, mixing of two powders.
Computer exercises followed by discussion. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Multivariate batch modelling. Computer exercises on API manufacture and reaction monitoring. Multivariate process modelling. Computer exercises and analysis of delegates' own data.
Course summary. |
| 16:00 |
End of course. |
Cost and conditions
Course fee is £1145 (+VAT) which includes lunch each day and the course dinner on Tuesday evening. The course will be held at our offices in Winkfield. B&B accommodation is available at the nearby Harte & Garter hotel in Windsor at preferential rates. Umetrics will organise accommodation at the hotel but delegates are responsible for settling their own bills. Cancellations received later than two weeks before the course starts will be charged at the full rate. Providing that Umetrics is notified, the registering company may substitute participants.
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
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US_EZinfo seminar 2007 ISPE
EZinfo Seminar at the 2007 Annual ISPE Conference
Where Umetrics will announce the release of our new product, EZinfo
You are cordially invited to Umetrics’ EZinfo Seminar which will be held in conjunction with the ISPE Conference in Las Vegas.
Flamingo Hotel, November 5 at 5:30 PM
Drinks and Hors d'Oeuvres will be provided.
Registration is required.
Please feel free to share this invitation with your manager and colleagues. All are welcome.
One Free EZinfo License will be given out to a lucky attendee.
EZinfo uses the power of Multivariate Analysis with a new approach, providing the immediate solution to your stated objective in the form of an active editable and customizable report. EZinfo is particularly suited for repetitive work, infrequent usage and non power users. In addition it simplifies communications across all levels of business and promotes knowledge transfer.
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US_MVA_Batch
Multivariate Analysis for Batch applications
Multivariate data analysis with projection methods is ideal for batch modelling, with the characteristic 3-way tables brought about by the batch maturity vector. Discover how to use the latest multivariate techniques to model batch processes and to interpret the models. You will see how models are applied to monitor batch evolution and predict batch quality before completion.
The course consists of lectures, examples and hands-on computer exercises in software SIMCA-P+, using real-life datasets.
After completing the course, participants will know how to:
• Understand the specific nature of batch data
• Be able to model batch data and interpret models in SIMCA-P+
• Be able to use models for prediction of batch quality
• Understand the concept of hierarchical modelling of batch data.
Who should participate?
The course is intended for researchers, scientists and engineers involved in research and development, production and manufacturing. Prior knowledge of Multivariate Data Analysis is preferable, but a review of the basic methodology will be given on the first day.
Course schedule
Lunch daily between 12:00 - 13:00
Day one
09:00 Review of MVA modelling, PCA, PLS MSPC objectives.
Objective of Batch modelling.
BMSPC, soft sensors.
Nature of batch data.
3-way decomposition vs unfolding with 2-way table analysis. Computer exercises followed by discussions.
18:00 End of lectures and exercises.
Day two
09:00 Hierarchical approach to modelling batch data.
What does quality of batch depend on?
Modelling batch data. Observation level. Batch level. Batch-specific issues. Representative training set.
Different phases. Scaling and centering of phases.
Run-to-run control. Time vs Maturity.
Smoothing maturity. Alignments of batches.
Demo using SIMCA-Batch On-Line.
Computer Exercises.
18:00 End of lectures and exercises.
Day three
09:00 Modelling batches in SIMCA-P+.
Import, specifying batch/phase identifiers.
Merging and deleting phases.
Local centering and filtering.
Conditional delete. Diagnostics and interpreting plots.
Control charts and transformations.
Prediction set and prediction control charts.
Creating batch level with different options.
Partial models and predicting the completed batch.
Model validation.
Conclusions. Course summary.
15:00 End of course.
Cost and conditions
Course fee includes coffee, lunch and course documentation. For an additional fee of $230 US, computer will be provided during course. To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy. |
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DOE , adv Mix design (hotel)
Design of Experiments for Mixtures
This one-day advanced course is dedicated to the special experimental situation when there is a mixture of components that add up to 100%. None of the ingredient amounts can be increased unless another is decreased. Hence, the factors are dependent of each other which adds to the complexity. Nevertheless, the formulations need design just as any other application - or even more.
The course is aimed at conveying the practicalities involved in performing designs of formulation, and how to handle results. The schedule will include both tutorial lectures and practical exercises in software MODDE, using well-established material from Umetrics AB. Additionally, course participants will be given the opportunity to work with their own data and to discuss analytical matters with the tutors.
After completing the course, participants will:
| • |
Be able to attack problems with new and refreshed skills in analysis
|
| • |
Have a deeper theoretical understanding of experimental design
|
| • |
Have discussed and exercised new areas of applications |
Who should participate?
The course is intended for those who have attended Umetrics Academy's design of experiments basic course, or have equivalent training or experience.
Course schedule
|
| 09:00 |
Course start.
Introduction.
A working strategy for mixture design.
Examples. |
| 12:00 |
Lunch |
| 13:00 |
Overview of mixture region.
Overview of mixture deisgn protocols.
Introduction to D-optimal design
Introduction to PLS.
Computer exercises and discussions.
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| 17:00 |
End of course.
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Cost and conditions
Course fee (+VAT) includes course documentation, lunch and coffee. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. OBSERVE THAT OWN LAPTOPS IS REQUIERED FOR EXCERCISES. PROGRAM INSTALLATION INSTRUCTIONS WILL BE SENT OUT WITH THE FINAL COURSE INFORMATION. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
information, please contact Umetrics Academy.
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MVA Omics 2d. Europe
Multivariate Analysis for "Omics"
Multivariate data analysis is essential in the process of extracting information from the complex data sets involved in “omics” studies. Discover how to build valid and predictive models based on data from genomic, proteomic and metabolomic studies, with the latest multivariate techniques. The focus on this course is how to use state-of art multivariate tools to extract putative biomarkers in a statistically significant way.
The course is composed of lectures, demonstrations and computer exercises using SIMCA-P+12 software on real-life datasets. Examples from plant biology and medicine will be used to highlight the usefulness of the applied strategies.
After completing the course, participants will know how to:
| • |
Insights on chemometrics strategies for ”omics” studies |
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Apply PCA to detect outliers, trends and patterns in "omics" data |
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An awareness of sources of variability and the effect on modeling and interpretation |
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Understanding of how to use OPLS in classification |
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Understanding on how to compare multiple treatments |
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Understanding on how to apply multivariate tools for putative biomarker identification |
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Validate models for robustness and predictability |
Who should participate?
The course is intended for researchers involved in “omics” studies with little or no knowledge in multivariate data analysis. The examples presented in the lectures are focused on MS- and NMR-based metabolomics, for consistency. The exercises include genomics, proteomics and metabolomics data sets so participants from different field can choose from their own interest. Practice on own data is also welcome and appreciated.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Introduction to multivariate data analysis
Principal component analysis, PCA
Apply PCA to detect outliers, trends and patterns in metabolomic data
Interpret models to gain scientific insights
Exercises in SIMCA-P+ |
| 17:00 |
End of lectures and exercises and course dinner |
| Day two |
| 09:00 |
From PCA to Orthogonal projections to latent structures, OPLS
Putative biomarkers identification using OPLS
How to compare multiple treatments
Validate models for robustness and predictability
Exercises in SIMCA-P+ and discussions
Course summary |
| 17:00 |
End of course |
Cost and conditions
Course fee (+VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
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Inhouse Design of Experiments
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
|
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
For further information, please contact Umetrics Academy.
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MVA for Spectroscopy
Multivariate Analysis (MVA) for Spectroscopic Applications
MVA and chemometrics are important tools for spectroscopy and Process Analytical Technology (PAT). Use of NIR spectra for qualitative and quantitative method requires MVA. This course starts with the basics of calibration and spectroscopy, including the data analysis covering statistics, regression, and MVA. Hands-on examples are used throughout the course. Students will construct calibration models for moisture, assay and classification. Related topics in equipment qualification and chemometric method validation will also be discussed. The course concludes with an application workshop, where students are encouraged to bring their own data sets for examination.
Instructor:
Frederick H. Long, Ph.D.
President, Spectroscopic Solutions, LLC
Dr. Long founded Spectroscopic Solutions, a PAT consulting and training firm, in 2001. His firm has done work for numerous pharmaceutical and consumer health companies including GSK, Novartis, Schering-Plough, Johnson & Johnson, Colgate-Palmolive, Actevis (world’s third largest generic drug firm). Dr. Long received his Ph.D. in Chemical Physics from Columbia University and a S.B. and S.M. in Physics from MIT.
After completing the course, each participant will be able to:
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Analyze their spectroscopic data |
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Produce validated calibration models using spectral information |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia who analyze spectroscopic data. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 08:30 |
Introduction to statistics
Regression analysis
Designed experiments
Linear algebra
Multivariate statistics |
| 17:00 |
End of lectures and exercises |
| Day two |
| 08:30 |
PCA
Introduction to NIR
Spectral pre-processing
PLS
Examples |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 8:30 |
Classification
Method Validation
Applications Workshop |
| 17:00 |
End of course |
Cost and conditions
Course fee includes coffee, lunch and course documentation. For an additional fee of $230 US, computer will be provided during course. To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
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US_IFPAC 2008
Please join us for a cocktail party at IFPAC 2008
You are cordially invited to Umetrics’ Evening Reception
Which will be held in conjunction with IFPAC 2008
Location
Baltimore Marriott Waterfront Hotel, January 29, 2008, at 7pm
(Same hotel as IFPAC), 700 Aliceanna Street, Baltimore, MD 21202
Program
SIMCA Batch On-Line (SBOL) Case Study presented by Merck & Co
Features of EZ Info and SIMCA-P+ version 12
Cocktails and Hors d'Oeuvres will be served.
All are welcome. Registration required.
There will be a raffle with a chance to win a FREE license of EZinfo.
--------------------------------------------------------------------------------
For more information, please contact:
Umetrics, Inc., 17 Kiel Avenue, Kinnelon, NJ 07405
973-492-8355, info.US@umetrics.com
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DOE Europe
Design of Experiments
Design of experiments is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using a minimum of resources. Discover how to optimise your company's experiments, products and processes for increased throughput and enhanced profitability.
The course splits between lectures and hands-on analysis of real data using Umetrics' state-of-the-art software package MODDE.
After completing the course, participants will know how to:
| • |
Create efficient designs to match the experimental objectives. |
| • |
Analyse experimental data using sound statistical principles. |
| • |
Improve and optimise products and processes. |
| • |
Report results in a simple graphical format. |
| • |
Design, measure, analyse, interpret, and optimize. |
| • |
Construct predictive models and apply them in practice |
Who should participate?
The course is intended for researchers, scientists and engineers from all sectors of industry and academia. No prior knowledge of statistics is assumed.
Course schedule
Lunch daily between 12:00 - 13:00 |
| Day one |
| 09:00 |
Course start.
How and when should design of experiments be used? Problem formulation, selection of goals, factors, responses, type of model and design.
Full factorials, the basis of other designs. Analysis of full factorial designs I, evaluation of raw data, regression analysis and model interpretation.
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day two |
| 09:00 |
Analysis of full factorials II. Fault detection.
Screening designs, which factors dominate and what are their optimal ranges.
What to do after screening, optimization or modification of the design. Optimization designs, how do we find an optimum or a compromise?
Computer exercises followed by discussions. |
| 17:00 |
End of lectures and exercises. |
| Day three |
| 09:00 |
Robustness testing, verification that the method or process is robust within given specifications.
Exercises using participants' or Umetrics' examples.
Discussion of participants' own data including creation of new designs.
Course summary. |
| 15:00 |
End of course. |
Cost and conditions
Course fee (+ VAT) includes coffee, lunch and course documentation. An invoice will be sent and payment is required within 30 days of the invoice date. Course application is binding. Cancellations registered later than two weeks before the course start will not be refunded. Provided that Umetrics AB is notified, the registering company may substitute its participant(s).
To register, please use the button "Begin registration" in this window frame, or send an email to Umetrics Academy.
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US_Webinar1
Start Time: 10:30am Pacific, 1:30pm Eastern.
Join us for a one-hour webinar on how Umetrics’ customers have created value by monitoring fermentation processes using SIMCA-Batch On-Line. See how you can easily bring this technology into your plant for improved productivity.
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US_Webinar2
Start Time: 10:30am Pacific, 1:30pm Eastern.
Join us for a one-hour webinar on how Umetrics’ customers have created value by analyzing plant data. From raw materials to r |
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Overview
