Supply Chains for Manufacturing: Capacity Analytics

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.

Course 6 of 8: Principles of Manufacturing 9 Weeks 10 - 12 Hours per week recommended

Please select the start dates for your courses below.

Scheduled Start:

About This Course:

As part of the Principles of Manufacturing MicroMasters program, this course focuses on decision making for system design, as it arises in manufacturing systems and supply chains.

You will learn about frameworks and models for structuring key system design issues and trade-offs that arise in today’s supply chains and manufacturing systems.

The course will also cover various models, methods and software tools for decision support for:

  • Logistics network design
  • Capacity planning and flexibility
  • Make-buy
  • Supply chain contracting
  • Supply chain risk mitigation

You will learn through industry applications and cases to illustrate concepts and challenges.This course should be taken in sequence following Supply Chains and Manufacturing Systems: Planning.

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:

  • Frameworks and models forsystem design
  • Decision supportmodels
  • Methods and software tools for supply chain contracting and risk mitigation


Supply Chains and Manufacturing Systems: Planning is required unless there is a strong prior knowledge of Logistics Systemsand Operations Management

Frequently Asked Questions:

For more information, please see the POM FAQ Page.

Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

Meet Your Instructors:

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.

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.


9 Weeks

Experience Level


Learning Partner

Massachusetts Institute of Technology



Program Type



Business & Management Data Analysis & Statistics Engineering