Experimental Designstatistical Methods for Process and Product improvementdesign of experimentsexperiment designdesigning experiments
Spécialisation Plan d'expériences
Design, Develop and Improve Products and Processes. Be able to apply modern experimental techniques to improve existing products and processes and bring new products and processes to market faster
Offert par
Spécialisation Plan d'expériencesUniversité d'État de l'ArizonaCe que vous allez apprendre
Plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain valid objective conclusions.
Use response surface methods for system optimization as a follow-up to successful screening.
Use experimental design tools for computer experiments, both deterministic and stochastic computer models.
Use software tools to create custom designs based on optimal design methodology for situations where standard designs are not easily applicable.
Compétences que vous acquerrez
À propos de ce Spécialisation
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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.
You can see an overview of the specialization from Dr. Montgomery here.
Projet d'apprentissage appliqué
Participants will complete a project that is typically based around their own work environment, and can use this to effectively demonstrate the application of experimental design methodology. The structure of the course and the step-by-stem process taught in the course is designed to ensure participant success.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
Cours en ligne à 100 %
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Planning flexible
Définissez et respectez des dates limites flexibles.
Niveau débutant
A previous course in basic statistical methods. The required background is introduced and reviewed as needed throughout the course.
Approx. 4 mois pour terminer
3 heures/semaine recommandées
Anglais
Sous-titres : Anglais, Arabe, Français, Portugais (européen), Chinois (simplifié), Italien, Vietnamien, Coréen, Allemand, Russe, Turc, Espagnol
Certificat partageable
Obtenez un Certificat lorsque vous terminez
Cours en ligne à 100 %
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Planning flexible
Définissez et respectez des dates limites flexibles.
Niveau débutant
A previous course in basic statistical methods. The required background is introduced and reviewed as needed throughout the course.
Approx. 4 mois pour terminer
3 heures/semaine recommandées
Anglais
Sous-titres : Anglais, Arabe, Français, Portugais (européen), Chinois (simplifié), Italien, Vietnamien, Coréen, Allemand, Russe, Turc, Espagnol
Cette Spécialisation compte 4 cours
Experimental Design Basics
89 évaluations
This is a basic course in designing experiments and analyzing the resulting data. The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Opportunities to use the principles taught in the course arise in all aspects of today’s industrial and business environment. Applications from various fields will be illustrated throughout the course. Computer software packages (JMP, Design-Expert, Minitab) will be used to implement the methods presented and will be illustrated extensively.
Factorial and Fractional Factorial Designs
32 évaluations
Many experiments in engineering, science and business involve several factors. This course is an introduction to these types of multifactor experiments. The appropriate experimental strategy for these situations is based on the factorial design, a type of experiment where factors are varied together. This course focuses on designing these types of experiments and on using the ANOVA for analyzing the resulting data. These types of experiments often include nuisance factors, and the blocking principle can be used in factorial designs to handle these situations. As the number of factors of interest grows full factorials become too expensive and fractional versions of the factorial design are useful. This course will cover the benefits of fractional factorials, along with methods for constructing and analyzing the data from these experiments.
Response Surfaces, Mixtures, and Model Building
35 évaluations
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.
Random Models, Nested and Split-plot Designs
23 évaluations
Many experiments involve factors whose levels are chosen at random. A well-know situation is the study of measurement systems to determine their capability. This course presents the design and analysis of these types of experiments, including modern methods for estimating the components of variability in these systems. The course also covers experiments with nested factors, and experiments with hard-to-change factors that require split-plot designs. We also provide an overview of designs for experiments with response distributions from nonnormal response distributions and experiments with covariates.
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.
Foire Aux Questions
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
Can I just enroll in a single course?
Puis-je m'inscrire à un seul cours ?
Can I take the course for free?
Puis-je suivre le cours gratuitement ?
Ce cours est-il vraiment accessible en ligne à 100 % ? Dois-je assister à certaines activités en personne ?
Quelle est la durée nécessaire pour terminer la Spécialisation ?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.
