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Manufacturing Process Control II

Learn how to control process variation, including methods to design experiments that capture process behavior and understand means to control variability.

Manufacturing Process Control II

There is one session available:

After a course session ends, it will be archived.
8,726 already enrolled!
Estimated 8 weeks
10–12 hours per week
Instructor-paced
Instructor-led on a course schedule
Free
Optional upgrade available

About this course

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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.

At a glance

  • Institution: MITx
  • Subject: Engineering
  • Level: Advanced
  • Prerequisites:

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

What you'll learn

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  • 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

Learner testimonials

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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!"

About the instructors

Frequently Asked Questions

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Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

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