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Using factorial design and multivariate analysis when experimenting in a continuous process
Author(s) -
Vanhatalo Erik,
Vännman Kerstin
Publication year - 2008
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.935
Subject(s) - multivariate statistics , factorial experiment , design of experiments , principal component analysis , process (computing) , factorial analysis , fractional factorial design , factorial , multivariate analysis , computer science , multivariate analysis of variance , statistics , engineering , operations research , mathematics , mathematical analysis , operating system
This article discusses the design and analysis of an experiment performed in a continuous process (CP). Three types of iron ore pellets are tested on two levels of a process variable in an experimental blast furnace process, using a full factorial design with replicates. A multivariate approach to the analysis of the experiment in the form of principal component analysis combined with analysis of variance is proposed. The analysis method also considers the split‐plot‐like structure of the experiment. The article exemplifies how a factorial design combined with multivariate analysis can be used to perform product development experiments in a CP. CPs also demand special considerations when planning, performing and analyzing experiments. The article highlights and discusses such issues and considerations, for example, the dynamic characteristic of CPs, a strategy to handle disturbances during experimentation and the need for process control during experimentation. Copyright © 2008 John Wiley & Sons, Ltd.