Fundamentals of Design of Experiments and Optimization: Designs for Factor Screening and Data Analysis in Pre-Response Surface Methodology
Fundamentals of Design of Experiments and Optimization: Designs for Factor Screening and Data Analysis in Pre-Response Surface Methodology
Chapter 2 presents an overview of the most important designs implemented for factor screening, including data analysis in pre-response surface methodology (pre-RSM). This chapter mainly focuses on practical aspects consid-ering a group of experimental factors at different levels at the same time, with a minimum number of experiments. Then it is discussed how to carry out studies in order to build an empirical model that correlates the information about factors and responses. Data analysis in pre-RSM is mostly represented by the well-known statistical method of multiway analysis of variance (ANOVA), whose basics are presented, together with the analysis of the validity of the results. In addition, two graphical strategies, the Pareto chart and the diagram of normal probability, are discussed. An example is used to illustrate the concepts. Suitable references are provided.
Fil: Azcarate, Silvana Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina
Fil: Chiappini, Fabricio Alejandro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Teglia, Carla Mariela. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
- National University of the Littoral Argentina
- National Scientific and Technical Research Council Argentina
- National University of La Pampa Argentina
DESIGN OF EXPERIMENTS, MULTIVARIATE OPTIMIZATION, https://purl.org/becyt/ford/1.4, FACTOR SCREENING, https://purl.org/becyt/ford/1, PRE-RESPONSE SURFACE METHODOLOGY
DESIGN OF EXPERIMENTS, MULTIVARIATE OPTIMIZATION, https://purl.org/becyt/ford/1.4, FACTOR SCREENING, https://purl.org/becyt/ford/1, PRE-RESPONSE SURFACE METHODOLOGY
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).2 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!