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Manufacturing Systems and Analysis
This course is part of Principles of Manufacturing MicroMasters.
This comprehensive course from MIT's top-ranked Mechanical Engineering department explores manufacturing systems analysis and optimization. Students learn to manage complex production systems, handle random events, and control inventory dynamics. The curriculum covers probability models, linear programming, queueing theory, and the Toyota Production System, providing essential skills for operations and supply chain management roles.
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What you'll learn
Apply probability models to analyze manufacturing systems
Develop and solve optimization models for production processes
Manage inventory dynamics effectively
Implement Toyota Production System principles
Analyze material and information flow in production lines
Optimize manufacturing system performance and cost control
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Module Description
This course provides comprehensive coverage of manufacturing systems analysis and optimization techniques. Beginning with probability and statistics fundamentals, it progresses through linear programming and queueing theory applications in manufacturing. The curriculum emphasizes practical aspects of inventory management and introduces the Toyota Production System principles. Students learn to analyze material flow, information systems, and handle random events in production environments. The course concludes with advanced stochastic manufacturing models developed at MIT.
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.
10 Courses
Manufacturing Systems Pioneer and Control Theory Expert
Stanley B. Gershwin has shaped manufacturing systems engineering through a remarkable career spanning over 45 years at MIT. After earning his B.S. in Engineering Mathematics from Columbia University and Ph.D. in Applied Mathematics from Harvard University, he began his journey through positions at Bell Labs and Draper Laboratory before joining MIT in 1972. As a Senior Research Scientist in MIT's Department of Mechanical Engineering, he developed groundbreaking mathematical methods for predicting and optimizing production line performance. His seminal work "Manufacturing Systems Engineering" (1994) became a cornerstone text in the field. Currently serving as Chief Scientific Officer at Dillygence since 2017, he continues to advance Industry 4.0 manufacturing solutions. His research contributions span manufacturing systems control, real-time scheduling, and decomposition methods for large-scale systems, earning him numerous accolades including IEEE Fellowship and multiple IIE Best Paper Awards. He has collaborated with major manufacturers including Boeing, General Motors, and Hewlett Packard, while developing the MIT Principles of Manufacturing online program. His work has garnered over 13,000 citations, reflecting his profound impact on manufacturing systems theory and practice.
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Frequently asked questions
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