This course is part of Principles of Manufacturing MicroMasters.
This foundational course from MIT's Mechanical Engineering department introduces statistical process control methods essential for manufacturing quality. Students learn to recognize and analyze inherent process variations, apply probability concepts, and develop structured approaches to quality control. The curriculum covers variation modeling, SPC foundations, and various control methods including Xbar, EWMA, and CUSUM. Through practical applications, students develop skills to achieve world-class manufacturing quality.
4
(36 ratings)
Instructors:
English
English
What you'll learn
Apply statistical methods to analyze manufacturing process variations
Implement Statistical Process Control techniques for quality improvement
Use Xbar EWMA and CUSUM methods for process monitoring
Assess process capability against design specifications
Develop strategies for achieving world-class manufacturing quality
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
Closed caption
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by

Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.





Module Description
This comprehensive course introduces statistical methods for controlling manufacturing process variations. Students learn to identify, model, and analyze inherent process variability using statistical tools and techniques. The curriculum covers essential topics including random process theory, Statistical Process Control (SPC) foundations, and various control methods such as Xbar, EWMA, and CUSUM. Emphasis is placed on practical applications for achieving consistent manufacturing quality through systematic variation control.
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Principles of Manufacturing MicroMasters
Instructors

9 Courses
Manufacturing Innovation Pioneer and Educational Leader at MIT
David Hardt has shaped manufacturing education and research at MIT for over four decades since joining the faculty in 1979 as the Ralph E. and Eloise F. Cross Professor of Mechanical Engineering. After earning his BSME from Lafayette College in 1972 and his SM and Ph.D. from MIT in 1978, he pioneered groundbreaking work in manufacturing process control and automation. His research spans multiple areas, from developing multivariable control techniques for gas metal arc welding to creating flexible tooling systems for aerospace applications. More recently, he has focused on polymer micro-embossing and large-scale additive manufacturing using recycled materials for low-cost housing. As Director of the MIT Laboratory for Manufacturing (1985-1992) and Engineering Co-Director of the Leaders for Manufacturing Program (1993-1998), he has significantly influenced manufacturing education. He led the development of MIT's first professional Master of Engineering in Manufacturing degree and the MITx MicroMasters Program in Principles of Manufacturing, which has awarded over 3,400 certificates. His international impact includes chairing the Singapore-MIT Alliance Program in Manufacturing Systems and Technology (1999-2014) and serving on the MIT Commission on Productivity in an Innovation Economy. His current research focuses on novel equipment design, process statistical control, and sustainable manufacturing solutions, while continuing to shape the future of manufacturing education through innovative programs and teaching methods.

8 Courses
Leader in Semiconductor Manufacturing and International Education
Duane Boning has established himself as a pioneering figure in semiconductor manufacturing and educational leadership at MIT, where he currently serves as Vice Provost for International Activities (effective September 2024) and the Clarence J. LeBel Professor in Electrical Engineering and Computer Science. After completing all his degrees at MIT (S.B. in EE and CS in 1984, S.M. in 1986, and Ph.D. in 1991), he briefly worked at Texas Instruments before joining the MIT faculty in 1992. His research focuses on machine learning and statistical methods for modeling semiconductor and photonic manufacturing processes, with over 300 publications to his credit. Throughout his career at MIT, he has held numerous leadership positions, including Associate Head of EECS (2004-2011), Director of the MIT Skoltech Initiative (2011-2013), and Faculty Director of the MIT/Masdar Institute Cooperative Program (2011-2018). As Engineering Faculty Co-Director of the MIT Leaders for Global Operations program since 2016, he has led the formation of MIT's Machine Intelligence for Manufacturing & Operations initiative. His contributions to semiconductor manufacturing have earned him IEEE Fellowship, while his expertise spans statistical modeling, process control, and variation analysis in IC, photonics, and MEMS processes. Currently, as Vice Provost for International Activities, he oversees MIT's global engagements while continuing his research in semiconductor manufacturing and design.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.