Title
A split-plot experiment with factor-dependent whole-plot sizes
Author
Schoen, E.
Jones, B.
Goos, P.
Publication year
2011
Abstract
Problem: The dairy company FrieslandCampina had an opportunity to redesign the production process for its coffee cream. This product has a very specific viscosity, and the redesigned process had to result in the same viscosity as the old one. Approach: For an effective redesign, the investigators wanted to obtain a simple model linking the settings of nine controllable factors to the viscosity of the product. They decided to use the results of a statistically designed experiment to build such a model. Two factors were hard to change (HTC) and could only be set six times; the remaining factors were easy to change (ETC). The presence of HTC and ETC factors calls for a split-plot experiment with whole plots defined by the six settings of the HTC factors. However, the number of runs within a whole plot depended on the level of one of the whole-plot factors. Commercial software fails to produce designs for this situation. In this paper, we detail orthogonal and nonorthogonal whole-plot designs for each of three total run sizes and discuss how three existing algorithms to construct optimal split-plot designs can be modified to handle factor-dependent whole-plot sizes. Results: The experiment was conducted according to one of the designs and viscosity measurements of the products were made. A second-order model, fitted using generalized least squares and restricted maximum likelihood, was used to study the effect of changes to the process design on the viscosity.
Subject
Life
QS - Quality & Safety
EELS - Earth, Environmental and Life Sciences
Nutrition
Coordinate-Exchange Algorithm
D-Optimum Designs
Point-Exchange Algorithm
Restricted Randomization
To reference this document use:
http://resolver.tudelft.nl/uuid:d9ca4251-a4bd-4daa-bdee-b65ef543237c
TNO identifier
427713
ISSN
0022-4065
Source
Journal of Quality Technology, 43 (1), 66-79
Document type
article