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MITx: Manufacturing Process Control I

Learn how to model variations in manufacturing processes and develop methods to reduce and control deterministic variations to achieve consistent process quality.

Manufacturing Process Control I
8 weeks
10–12 hours per week
Instructor-paced
Instructor-led on a course schedule
This course is archived
Future dates to be announced

About this course

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Randomness is inherent in all processes including manufacturing. The fundamental concepts taught in this course will help learners develop powerful statistical process control methods that are the foundation of world-class manufacturing quality.

As part of the Principles of Manufacturing MicroMasters program, this course will introduce statistical methods that apply to any unit manufacturing process. We will cover the following topics:

  • Recognizing inherent variability in continuous production
  • Identifying sources of process output variation
  • Describing variation in a structured manner
  • Applying basic probability and statistics concepts to characterize process variation
  • Differentiating between design specifications and process capability
  • Synthesizing novel approaches to unfamiliar situations by extending the core material (i.e. go beyond the “standard” uses).
  • Assessing the appropriateness of various statistical methods for a variety of problems

Develop the engineering and management 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 will earn the MicroMasters Credential and qualify to apply to gain credit towards MIT’s Master of Engineering in Advanced Manufacturing & Design program.

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At a glance

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

    Engineering Undergraduate preparation; some knowledge of basic manufacturing processes. Knowledge or probability theory is helpful but not necessary.

  • Associated programs:
  • Language: English
  • Video Transcript: English
  • Associated skills:Statistical Process Controls, Manufacturing Processes, Statistical Methods, Advanced Manufacturing, Management, Probability And Statistics, Sales, Mechanical Engineering, Design Specifications, Deterministic Methods

What you'll learn

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  • Variation modeling using the theory of Random Processes
  • Statistical Process Control (SPC) foundations and applications
  • Xbar, EWMA, CUSUM and discrete event methods for detecting process problems
  • Methods for analyzing process changes by looking at general process physics
  • How to apply these methods to achieve world-class quality in unit manufacturing processes

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!"

Frequently Asked Questions

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For more information, please see the POM FAQ Page.

Who can take this course?

Unfortunately, learners residing in 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.

This course is part of Principles of Manufacturing MicroMasters Program

Learn more 
Expert instruction
8 graduate-level courses
Instructor-led
Assignments and exams have specific due dates
1 year 5 months
10 - 12 hours per week

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