Factorial experiments are often used in factor screening.; that is, identify the subset of factors in a process or system that are of primary important to the response. Once the set of important factors are identified interest then usually turns to optimization; that is, what levels of the important factors produce the best values of the response. This course provides design and optimization tools to answer that questions using the response surface framework. Other related topics include design and analysis of computer experiments, experiments with mixtures, and experimental strategies to reduce the effect of uncontrollable factors on unwanted variability in the response.
Este curso faz parte do Programa de cursos integrados Criação de experimentos
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Programa de cursos integrados Criação de experimentosUniversidade do Estado do ArizonaInformações sobre o curso
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Prazos flexíveis
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Curso 3 de 4 no
Nível intermediário
Aprox. 13 horas para completar
Inglês
Legendas: Francês, Portuguese (European), Russo, Inglês, Espanhol
O que você vai aprender
Conduct experiments w/computer models and understand how least squares regression is used to build an empirical model from experimental design data
Understand the response surface methodology strategy to conduct experiments where system optimization is the objective
Recognize how the response surface approach can be used for experiments where the factors are the components of a mixture
Recognize where the objective of the experiment is to minimize the variability transmitted into the response from uncontrollable factors
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 3 de 4 no
Nível intermediário
Aprox. 13 horas para completar
Inglês
Legendas: Francês, Portuguese (European), Russo, Inglês, Espanhol
oferecido por
Universidade do Estado do Arizona
Arizona State University has developed a new model for the American Research University, creating an institution that is committed to excellence, access and impact. ASU measures itself by those it includes, not by those it excludes. ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it.
Programa - O que você aprenderá com este curso
5 horas para concluir
Unit 1: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
5 horas para concluir
12 vídeos (Total 125 mín.), 4 leituras, 3 testes
2 horas para concluir
Unit 2: Regression Models
2 horas para concluir
7 vídeos (Total 98 mín.), 1 leitura, 2 testes
4 horas para concluir
Unit 3: Response Surface Methods and Designs
4 horas para concluir
14 vídeos (Total 178 mín.), 1 leitura, 2 testes
2 horas para concluir
Unit 4: Robust Parameter Design and Process Robustness Studies
2 horas para concluir
4 vídeos (Total 39 mín.), 1 leitura, 2 testes
Avaliações
- 5 stars79,59%
- 4 stars8,16%
- 3 stars10,20%
- 2 stars2,04%
Principais avaliações do RESPONSE SURFACES, MIXTURES, AND MODEL BUILDING
por RR25 de jul de 2020
It was a great experience for me to do the RSM model building an online course. I learned experimental designs for fitting response surfaces.
por AZ9 de out de 2021
DoE is an essential but forgotten initial step in the experimental work! This course gives a very good start and breaking the ice for higher quality of experimental work.
Sobre Programa de cursos integrados Criação de experimentos
Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
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