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.
Ce cours fait partie de la Spécialisation Plan d'expériences
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Spécialisation Plan d'expériencesUniversité d'État de l'ArizonaÀ propos de ce cours
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Cours 3 sur 4 dans le
Niveau intermédiaire
Approx. 13 heures pour terminer
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Sous-titres : Français, Portugais (européen), Russe, Anglais, Espagnol
Ce que vous allez apprendre
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
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 4 dans le
Niveau intermédiaire
Approx. 13 heures pour terminer
Anglais
Sous-titres : Français, Portugais (européen), Russe, Anglais, Espagnol
Offert par
Université d'État de l'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.
Programme de cours : ce que vous apprendrez dans ce cours
5 heures pour terminer
Unit 1: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
5 heures pour terminer
12 vidéos (Total 125 min), 4 lectures, 3 quiz
2 heures pour terminer
Unit 2: Regression Models
2 heures pour terminer
7 vidéos (Total 98 min), 1 lecture, 2 quiz
4 heures pour terminer
Unit 3: Response Surface Methods and Designs
4 heures pour terminer
14 vidéos (Total 178 min), 1 lecture, 2 quiz
2 heures pour terminer
Unit 4: Robust Parameter Design and Process Robustness Studies
2 heures pour terminer
4 vidéos (Total 39 min), 1 lecture, 2 quiz
Avis
- 5 stars79,59 %
- 4 stars8,16 %
- 3 stars10,20 %
- 2 stars2,04 %
Meilleurs avis pour RESPONSE SURFACES, MIXTURES, AND MODEL BUILDING
par RR25 juil. 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.
par AZ9 oct. 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.
À propos du Spécialisation Plan d'expériences
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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