Program Overview
Develop the fundamental skills needed for global excellence in manufacturing and competitiveness with the Principles of Manufacturing MicroMasters Credential, designed and delivered by MIT’s #1-world ranked Mechanical Engineering department.
This program provides students with a fundamental basis for understanding and controlling rate, quality and cost in a manufacturing enterprise.
The Principles of Manufacturing are a set of elements common to all manufacturing industries that revolve around the concepts of flow and variations. These principles have emerged from working closely with manufacturing industries at both the research and operational levels.
Targeted towards graduate-level engineers, product designers, and technology developers with an interest in a career in advanced manufacturing, the program will help learners understand and apply these principles to product and process design, factory and supply chain design, and factory operations.
This curriculum focusses on the analysis, characterization and control of flow and variation at different levels of the enterprise through the following subject areas:
- Unit Process Variation and Control: Modeling and controlling temporal and spatial variation in unit processes
- Factory Level System Variation and Control: Modeling and controlling flows in manufacturing systems with stochastic elements and inputs.
- Supply Chain – System Variation and Control: How to operate and design optimal manufacturing-centered supply chains.
- Business Flows: Understanding the uses and flow of business information to start up, scale up and operate a manufacturing facility.
What you will learn
- A new perspective for design and operational decision making at all levels of manufacturing, in the context of volume manufacturing, where rate, quality, cost and flexibility are the key metrics
- How to operate and control unit processes to ensure maximum quality using basic and advanced statistical and feedback control methods
- How to design and operate systems of processes with optimal capacity, resilience and inventory
- How to design and operate optimal supply chain systems
- The financial underpinnings of a manufacturing enterprise, including new ventures
Program Class List
1Manufacturing Process Control I
Course Details
1
Learn how to model variations in manufacturing processes and develop methods to reduce and control deterministic variations to achieve consistent process quality.
2Manufacturing Systems I
Course Details
2
Learn about manufacturing systems and ways to analyze them in terms of material flow and storage, information flow, capacities, and times and durations of events, especially random events.
3Management in Engineering: Accounting and Planning
Course Details
3
Experience what it is like to manage within an engineering enterprise. Develop the business skills you need to take on the variety of challenges facing managers in the field. This course was formerly known as Management in Engineering I.
4Supply Chains for Manufacturing: Inventory Analytics
Course Details
4
Learn about effective supply chain strategies for companies that operate globally, with emphasis on how to plan and integrate supply chain components into a coordinated system. This course was formerly known as Supply Chains for Manufacturing I.
5Manufacturing Process Control II
Course Details
5
Learn how to control process variation, including methods to design experiments that capture process behavior and understand means to control variability.
6Supply Chains for Manufacturing: Capacity Analytics
Course Details
6
Learn about various models, methods and software tools to help make better decisions for system design in manufacturing systems and supply chains.. This course was formerly known as Supply Chains for Manufacturing II.
7Manufacturing Systems II
Course Details
7
Learn how to analyze manufacturing systems to optimize performance and control costs and better understand the flow of material and information.
8Management in Engineering: Strategy and Leadership
Course Details
8
Analyze challenging real-life business cases that engineering managers face on a variety of topics. Apply management tools and relevant skills to manage innovation. This course was formerly known as Management in Engineering II
Meet Your Instructors
Stanley B. Gershwin
Senior Research Scientist at Massachusetts Institute of Technology
Stanley B. Gershwin is a Senior Research Scientist at the MIT Department of Mechanical Engineering. He received the B.S. degree in Engineering Mathematics from Columbia University, New York, New York, in 1966; and the M.A. and Ph.D. degrees in Applied Mathematics from Harvard University, Cambridge, Massachusetts, in 1967 and 1971.
Sean Willems
Haslam Chair in Supply Chain Analytics at University of Tennessee
Sean Willems is the Haslam Chair in Supply Chain Analytics at the University of Tennessee's Haslam College of Business. In 2000, he co-founded Optiant, a provider of multi-echelon inventory optimization tools, which was later acquired by Logility, Inc. He has been a visiting professor of operations management at the MIT Sloan School of Management since 2016. His work with companies such as Hewlett Packard, Proctor & Gamble, and Intel has led to finalist selections for the 2003, 2010, and 2017 Franz Edelman Award for Achievement in Operations Research and the Management Sciences.
Jung-Hoon Chun
Professor of Mechanical Engineering at Massachusetts Institute of Technology
Jung-Hoon Chun is director of the Laboratory for Manufacturing and Productivity and a professor of mechanical engineering at the Massachusetts Institute of Technology (MIT). He has been a member of the MIT Mechanical Engineering faculty since 1989, and has over 100 publications and patents to his credit.
Stephen Graves
Abraham J. Siegel Professor of Management at Massachusetts Institute of Technology
Stephen Graves is the Abraham J. Siegel Professor of Management and a Professor of Operations Management at the MIT Sloan School of Management. He has a joint appoitnemnt with the MIT Department of Mechanical Engineering. Graves develops and applies operations research models and methods to solve problems in manufacturing and distribution systems and in service operations. Graves holds an AB in mathematics and social sciences and an MBA from Dartmouth College, and an MS and a PhD from the University of Rochester.
Duane Boning
Co-Director, MIT Leaders for Global Operations Program at Massachusetts Institute of Technology
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 currently Director of the MIT/Masdar Institute Cooperative Program. Dr. Boning received his S.B. degrees in electrical engineering and in computer science in 1984, and his S.M. and Ph.D. degrees in electrical engineering in 1986 and 1991, respectively, all from the Massachusetts Institute of Technology.
David Hardt
Ralph E. and Evelyn F. Cross Professor of Mechanical Engineering at Massachusetts Institute of Technology
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 dynamics and control as applied to manufacturing.
Abbott Weiss
Senior Lecturer, Supply Chain Management at Massachusetts Institute of Technology
Throughout his career, Abbott Weiss has been on the leading edge of supply chain thinking and practice--designing and executing powerful business solutions integrating multi-billion dollar global transportation, logistics, order fulfillment, manufacturing, customer services, planning, and materials systems. He is currently a consultant and a Senior Lecturer at MIT in supply chain management.
About This Course:
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.
What You’ll 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
MicroMasters® Program in Principles of Manufacturing
Learn from the world’s #1 ranked Mechanical Engineering department
Manufacturing Process Control I
Manufacturing Systems I
Management in Engineering: Accounting and Planning
Supply Chains for Manufacturing: Inventory Analytics
Manufacturing Process Control II
Supply Chains for Manufacturing: Capacity Analytics
Manufacturing Systems II
Management in Engineering: Strategy and Leadership
Prerequisites:
- Engineering Undergraduate preparation
- Some knowledge of basic manufacturing processes
- Knowledge or probability theory is helpful but not necessary
Meet Your Instructors:
David Hardt
Ralph E. and Evelyn F. Cross Professor of Mechanical Engineering at Massachusetts Institute of Technology
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 dynamics and control as applied to manufacturing.
Duane Boning
Co-Director, MIT Leaders for Global Operations Program at Massachusetts Institute of Technology
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 currently Director of the MIT/Masdar Institute Cooperative Program. Dr. Boning received his S.B. degrees in electrical engineering and in computer science in 1984, and his S.M. and Ph.D. degrees in electrical engineering in 1986 and 1991, respectively, all from the Massachusetts Institute of Technology.
