Management
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Manufacturing Process Control I

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Course Features

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Duration

8 weeks

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Effort

12 hours per week

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Teaching Type

Instructor Paced

Course Description

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.

Course Overview

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Live Class

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Human Interaction

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Personlized Teaching

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Engineering Undergraduate preparation

some knowledge of basic manufacturing processes

Knowledge or probability theory is helpful but not necessary.

What You Will Learn

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

Course Instructors

Duane Boning

Co-Director, MIT Leaders for Global Operations Program

Dr. Duane S. Boning is the Clarence J. LeBel Professor in Electrical Engineering, and Professor of Electrical Engineering and Computer Science in the EECS Department at MIT. He is affiliated with the...

David Hardt

Ralph E. and Evelyn F. Cross Professor of Mechanical Engineering

Professor Hardt is a graduate of Lafayette College (BSME, 1972) and MIT (SM, PhD, 1978). He has been a member of the Mechanical Engineering faculty at MIT since 1979. His disciplinary focus is system...
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