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ALLSTAT  1999

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Subject:

COURSES: Presented by Dr Douglas Montgomery

From:

Kellie Watkins <[log in to unmask]>

Reply-To:

Kellie Watkins <[log in to unmask]>

Date:

Fri, 30 Apr 1999 14:40:48 +0100

Content-Type:

text/plain

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text/plain (77 lines)

Presented by Dr Douglas C. Montgomery, Arizona State University, USA

We are announcing the following two short courses, to be held at the
Statistical Services Centre, The University of Reading, UK:

Statistical Process Control - Beyond the Basics
19-21 May
Response Surface Methodology: Process and Product Optimization Using
Designed Experiments
24-27 May


For further information and registration details please contact Kellie
Watkins at The University of Reading ([log in to unmask]), providing
an address and/or fax number.

____________________________________________________________________________
_________________________

* Statistical Process Control - Beyond the Basics *
19-21 May 1999

This is an intermediate level course in statistical process control and
other techniques for statistical process monitoring and improvement. The
course assumes familiarity with basic Shewhart control charts, and is
intended for engineers, technical managers, statisticians, and other
process specialists who are interested in expanding the tools that they can
apply.

Statistical process control concepts are reviewed and various different
control charts such as Shewhart, cumulative sum (CUSUM) and exponentially
weighted moving average (EWMA) are all discussed. Other topics include
monitoring processes with autocorrelated data, process monitoring and
process regulation, multivariate process monitoring and control, and
capability analysis. The use of computer software to implement the changes
is discussed and illustrated.


* Response Surface Methodology: Process and Product Optimization Using
Designed Experiments *
24-27 May 1999

Experimental design methods based on the factorial strategy are used
extensively in industry. These experiments usually have system (product or
process) characterisation as their objective. That is, finding the key
variables that influence the output of the system. Once the key process
variables have been identified, the experimenters objective usually becomes
system optimisation; that is, finding the setting of the important
variables that result in the best or ideal system performance. Response
surface methodology (RSM) is a powerful collection of experimental design,
modelling and optimisation techniques for accomplishing these objectives.

This course is a comprehensive introduction to RSM, including the strategy
of RSM, basic experimental designs and optimisation techniques, and methods
for simulataneously optimising several responses of interest. Two
important extensions of RSM, robust process design and experiments with
mixture systems, are also discussed. Mixture experiments are particularly
useful for product formulators, but also have extensive application in
process and manufacturing settings, such as plating and etching. Computer
software for planning and analysing RSM experiments is illustrated
extensively throughout the course.

Kellie Watkins
Statistical Services Centre
The University of Reading
Harry Pitt Building
PO Box 240
Whiteknights Road
Reading RG6 6FN
UK

Tel: +44 (0)118 931 8689
Fax: +44 (0)118 975 3169


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