Designing industrial experiments with restricted experimental resources


Sexton, Christine June (1998) Designing industrial experiments with restricted experimental resources. University of Southampton, Department of Mathematics, Doctoral Thesis , 242pp.

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Description/Abstract

This thesis presents two procedures for designing industrial experiments with
restricted experimental resources. First, a two-stage approach is developed using
the D- and Ds-optimality criteria in combination, to focus information into the
effects of most relevance to the robust engineering design of a product. The
method is demonstrated by finding a design for a study on gas sensors.
The second approach forms the major contribution of this thesis. Semicontrolled
experiments are developed for use in situations where the factor values
cannot be pre-determined, although the way in which they are combined with
other factors can be controlled. This situation arises when the costs of measuring
components in a product, or of making one-off components, prevents the use of
a conventional factorial experiment. In the method, samples of the components
are obtained and features of interest are measured. The components are then
combined in products for testing to give combinations of the factor values which
will maximise the information on the factorial effects under investigation. This
method is particularly useful when derived factors, that is, factors defined as functions
of variables from one or more components, are of engineering interest. An
exchange algorithm is presented for finding optimal designs for semi-controlled
experiments and demonstrated on a small pilot study on a gear pump.
An extension of the algorithm is provided to design experiments when some
factors can be pre-set in the conventional way, but others cannot. The issues of
power and the size of experiment for a semi-controlled study are also addressed
through simulated experiments.

Item Type: Thesis (Doctoral)
Additional Information: In back pocket: diskette
Subjects: Q Science > QA Mathematics
H Social Sciences > HD Industries. Land use. Labor
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: University Structure - Pre August 2011 > School of Mathematics
ePrint ID: 50646
Date Deposited: 06 Apr 2008
Last Modified: 27 Mar 2014 18:34
URI: http://eprints.soton.ac.uk/id/eprint/50646

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