期刊
出版社
ELSEVIER
DOI: 10.1016/j.jchromb.2012.01.020
关键词
Experimental design; Design of experiments (DoE); Response surface methodology; Method validation; Optimisation Plackett-Burman design; Central composite design; Box-Behnken design; Mixture design; Doehlert design; Factorial design; Fractional factorial design
The ability of a chromatographic method to successful separate, identify and quantitate species is determined by many factors, many of which are in the control of the experimenter. When attempting to discover the important factors and then optimise a response by tuning these factors, experimental design (design of experiments. DoE) gives a powerful suite of statistical methodology. Advantages include modelling by empirical functions, not requiring detailed knowledge of the underlying physico-chemical properties of the system, a defined number of experiments to be performed, and available software to accomplish the task. Two uses of DoE in chromatography are for showing lack of significant effects in robustness studies for method validation, and for identifying significant factors and then optimising a response with respect to them in method development. Plackett-Burman designs are widely used in validation studies, and fractional factorial designs and their extensions such as central composite designs are the most popular optimisers. Box-Behnken and Doehlert designs are becoming more used as efficient alternatives. lilt is not possible to practically realise values of the factors required by experimental designs, or if there is a constraint on the total number of experiments that can be done, then D-optimal designs can be very powerful. Examples of the use of DoE in chromatography are reviewed. Recommendations are given on how to report DoE studies in the literature. (c) 2012 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据