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 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.

A Course Conducted by MITx

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Meet your instructors

Stanley B. Gershwin

Stanley B. Gershwin is a Senior Research Scientist at the MIT Department of Mechanical Engineering. He received a 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. In 1970-71, he was employed by the Bell Telephone Laboratories in New Jersey, where he studied telephone hardware capacity estimation. At the C. S. Draper Laboratory in Cambridge, Massachusetts, from 1971-75, he investigated problems in manufacturing and in transportation. He worked in the MIT Laboratory for Information and Decision Systems (LIDS) during 1975-1987. He was a Professor of Manufacturing Engineering at the Boston University College of Engineering (half time) in 1986-1987. Dr. Gershwin currently teaches an MIT course in Manufacturing Systems Analysis (2.852). He has been a member of the MIT Laboratory for Manufacturing and Productivity since 1988. Dr. Gershwin is the author of Manufacturing Systems Engineering (Prentice-Hall, 1994) and numerous papers in international journals. The Institute of Industrial Engineers has given two awards for his paper “Design and Operation of Manufacturing Systems — The Control-Point Policy,” (IIE Transactions, Volume 32, Number 2, pp. 891-906, October 2000) the Best Paper Award for the IIE Transactions focus issues on Design and Manufacturing for 2000-2001, and the Outstanding IIE Publication Award for 2000-2001. An article has appeared in IIE Solutions on Dr. Gershwin and these awards. The Institute of Industrial Engineers has selected “Information inaccuracy in inventory systems: stock loss and stockout,” (IIE Transactions, Volume 37, Number 9, September 2005, pp. 843­859) by Yun Kang and Stanley B. Gershwin for the Best Paper of the Year in IIE Transactions on Design & Manufacturing. His research interests include real-time scheduling and planning in manufacturing systems; hierarchical control; dynamic programming in hybrid (discrete and continuous state) systems; decomposition methods for large scale systems; approximation techniques. His major research goal is the development of an engineering theory of manufacturing systems control. Dr. Gershwin and his students have performed research projects and consulted for such companies as Boeing, General Motors, Polaroid, Hewlett Packard, Johnson & Johnson, United Technologies, and others. Dr. Gershwin is a member of the IEEE Control Systems Society, the IEEE Robotics and Automation Society, the Operations Research Society of America, the Institute of Industrial Engineers, and the Society of Manufacturing Engineers. He has been an Associate Editor of several international journals, including the International Journal of Production Research, Operations Research, IEEE Transactions on Automatic Control, and others. Dr. Gershwin was an IEEE Control Systems Society Distinguished Lecturer and is a Fellow of the IEEE. Dr. Gershwin is affiliated with MIT’s Laboratory for Manufacturing and Productivity, Leaders for Manufacturing Program, and the Operations Research Center.

Duane Boning

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 MIT Microsystems Technology Laboratories and serves as MTL Associate Director for Computation and CAD. From 2004 to 2011, he served as Associate Head of the EECS Department at MIT, and from 2011 through 2013 as Director/Faculty Lead of the MIT Skoltech Initiative. He is currently the 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. He was an NSF Fellow from 1984 to 1989, and an Intel Graduate Fellow in 1990. From 1991 to 1993 he was a Member Technical Staff at the Texas Instruments Semiconductor Process and Design Center in Dallas, Texas, where he worked on semiconductor process representation, process/device simulation tool integration, and statistical modeling and optimization. Dr. Boning is a Fellow of the IEEE and has served as Editor in Chief for the IEEE Transactions on Semiconductor Manufacturing and as chairman of the CFI/Technology CAD Framework Semiconductor Process Representation Working Group. He is a member of the IEEE, Electrochemical Society, Eta Kappa Nu, Tau Beta Pi, Materials Research Society, Sigma Xi, and the Association of Computing Machinery.

Sean Willems

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. He has been a finalist in 2006, 2008 and 2012 for the Daniel H. Wagner Prize for Excellence in Operations Research Practice. His work on inventory placement under non-stationary demand won the Wagner Prize in 2008. Willems is the department editor of the practice section of the journal Production and Operations Management and he is the deputy editor of Interfaces. He received his bachelor’s degree in decision sciences from the University of Pennsylvania’s Wharton School and his master’s in operations research and a doctorate in operations management from the MIT Sloan School of Management.

David Hardt

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. His research has been on flexible automation, and process control, with a historical emphasis on welding and forming processes, and a current focus on polymer micro embossing. In welding, he pioneered the use of multivariable control techniques for modeling and control of GMAW and demonstrated the use of adaptive control in these systems. In the forming processes, he concentrated on the use of in-process measurements and real-time modeling to reduce sensitivity to the machine and material variations and has developed a flexible tooling and closed-loop shape control that has implemented in the aerospace industry with specific uses for repair part manufacture. His more recent work has been in the hot micro-embossing process for microfluidic device manufacture and scale-up of soft lithography methods using roll to roll processes. In both cases, the theme of the work is novel equipment design and overall equipment and process statistical control Prof. Hardt has taught classes in both Mechanical Engineering and Manufacturing and has led the creation of a new graduate degree: Master of Engineering in Manufacturing” at MIT. This is the first professional degree offered by the ME Department at MIT and is the culmination of many years of course and curriculum development. Prof. Hardt served as Director of the MIT Laboratory for Manufacturing from 1985 – 1992 and as Engineering Co-Director for the MIT Leaders for Manufacturing Program from 1993 to 1998. From 1999 to 2011 he was the MIT Chair of the Singapore MIT Alliance (SMA) Program: “Manufacturing Systems and Technology”, a research and teaching collaboration with Nanyang Technological University in Singapore. He was a member of the MIT Commission on Productivity in an Innovation Economy and served on the Workforce team on the Advanced Manufacturing Partnership Program (AMP 1.0).

Jung-Hoon Chun

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. His research focuses on the development of Innovative Manufacturing Processes. His research areas include droplet-based manufacturing processes, microelectronics manufacturing processes such as chemical-mechanical polishing and polymer-based microfluidic devices manufacturing. One of his patented manufacturing processes, the uniform-droplet spray process, has been commercialized worldwide for the production of solder spheres used in electronics packaging. His teaching focuses on these research areas and on management in engineering. Dr. Chun also has experience in many large-scale international collaborations and industry-MIT consortia. He is active in advising and consulting for many for-profit and non-profit organizations worldwide, in technical as well as policy areas. Dr. Chun received a B.S. from Seoul National University, an M.A.Sc. from the University of Ottawa, and a Ph.D. from MIT, all in mechanical engineering.

Abbott Weiss

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.

Stephen Graves

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 appointment 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. His current research is focused on operational issues arising in online retailing, supply chain optimization and strategic inventory positioning, and production and capacity planning for various contexts. Graves holds an AB in mathematics and social sciences and an MBA from Dartmouth College, and an MS and a Ph.D. from the University of Rochester.