• Duración:
    8 semanas
  • Dedicación:
    10–12 horas por semana
  • Precio:

    GRATIS
    Agregar un Certificado Verificado por $175 USD

  • Institución
  • Tema:
  • Nivel:
    Advanced
  • Idioma:
    English
  • Transcripción de video:
    English
  • Tipo de curso:
    Al ritmo del instructor

Programas asociados:

Prerrequisitos

Manufacturing Process Control I is required unless there is a strong prior knowledge of statistical methods and SPC.

Sobre este curso

Omitir Sobre este curso

As part of the Principles of Manufacturing MicroMasters program, this course will build on statistical process control foundations to add process modeling and optimization.Building on formal methods of designed experiments, the course develops highly applicable methods for creating robust processes with optimal quality.

We will cover the following topics:

  • Evaluating the causality of inputs and parameters on the output measures
  • Designing experiments for the purpose of process improvement
  • Methods for optimizing processes and achieving robustness to noise inputs
  • How to integrate all of these methods into an overall approach to process control that can be widely applied
  • Developing a data-based statistical ability to solving engineering problems in general

The course will conclude with a capstone activity that will integrate all the Statistical Process Control topics.

Develop the engineering andmanagement skills needed for competence and competitiveness in today’s manufacturing industry with the Principles of Manufacturing MicroMasters Credential, designed and delivered by MIT’s #1-ranked Mechanical Engineering department in the world. Learners who pass the 8 courses in the program earn the MicroMasters Credential and qualify to apply to gain credit for MIT’s Master of Engineering in Advanced Manufacturing & Design program.

Lo que aprenderás

Omitir Lo que aprenderás
  • Multivariate regression for Input-output causality
  • Design of experiments (DOE) methods to improve processes
  • Response surface methods and process optimization based on DOE methods
  • DOE-based methods for achieving processes that are robust to external variations

Conoce a tus instructores

Duane Boning
Co-Director, MIT Leaders for Global Operations Program
Massachusetts Institute of Technology
David Hardt
Ralph E. and Evelyn F. Cross Professor of Mechanical Engineering
Massachusetts Institute of Technology

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Testimonios de los estudiantes

From the on-campus version:
“2.830 lectures are immensely helpful in my day to day job responsibilities. I can now better understand the concepts of quality and drive quality improvements based on that.”

“Thanks – I use 2.830 everyday!”

"We're talking about process capability Cpk, we're talking about AQL sampling, we're talking about how we will know if vendor and internal processes are stable, etc. Real life application of the stuff I learned from 2.830!"

Preguntas frecuentes

For more information, please see the POM FAQ Page.

¿Quién puede hacer este curso?

Lamentablemente, las personas de uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.