Experimental Designstatistical Methods for Process and Product improvementdesign of experimentsexperiment designdesigning experiments
Programa especializado: Diseño experimental
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
ofrecido por
Programa especializado: Diseño experimentalUniversidad del Estado de ArizonaQué aprenderás
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.
Habilidades que obtendrás
Acerca de este Programa Especializado
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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.
Proyecto de aprendizaje aplicado
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.
Certificado para compartir
Obtén un certificado al finalizar
Cursos 100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Cronograma flexible
Establece y mantén fechas de entrega flexibles.
Nivel principiante
A previous course in basic statistical methods. The required background is introduced and reviewed as needed throughout the course.
Aprox. 4 meses para completar
Sugerido 3 horas/semana
Inglés (English)
Subtítulos: Inglés (English), Árabe (Arabic), Francés (French), Portugués (de Brasil), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Turco (Turkish), Español (Spanish), Chino (Chinese)
Certificado para compartir
Obtén un certificado al finalizar
Cursos 100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Cronograma flexible
Establece y mantén fechas de entrega flexibles.
Nivel principiante
A previous course in basic statistical methods. The required background is introduced and reviewed as needed throughout the course.
Aprox. 4 meses para completar
Sugerido 3 horas/semana
Inglés (English)
Subtítulos: Inglés (English), Árabe (Arabic), Francés (French), Portugués (de Brasil), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Turco (Turkish), Español (Spanish), Chino (Chinese)
Hay 4 cursos en este Programa Especializado
Experimental Design Basics
79 calificaciones
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
25 calificaciones
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
32 calificaciones
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
17 calificaciones
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.
ofrecido por
Universidad del Estado de 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.
Preguntas Frecuentes
¿Recibiré crédito universitario por completar el programa especializado?
Can I just enroll in a single course?
¿Puedo inscribirme en un solo curso?
Can I take the course for free?
¿Puedo tomar este curso de manera gratuita?
¿Este curso es 100 % en línea? ¿Necesito asistir a alguna clase en persona?
¿Cuánto tiempo se necesita para completar un programa especializado?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
¿Recibiré crédito universitario por completar el programa especializado?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.
