Course Description

Welcome to the advanced Manufacturing Process Control II course, a vital component of the Principles of Manufacturing MicroMasters program offered by MIT's top-ranked Mechanical Engineering department. This course builds upon the foundations of statistical process control and introduces students to cutting-edge techniques in process modeling and optimization. By mastering these advanced concepts, you'll gain a competitive edge in today's manufacturing industry and develop crucial engineering and management skills.

What students will learn

• Multivariate regression for input-output causality analysis
• Design of experiments (DOE) methods for process improvement
• Response surface methods and process optimization based on DOE
• DOE-based techniques for creating robust processes resistant to external variations
• Evaluation of input and parameter effects on output measures
• Integration of statistical methods into a comprehensive process control approach
• Data-driven statistical problem-solving skills for engineering applications

Pre-requisites

Students should have completed Manufacturing Process Control I or possess strong prior knowledge of statistical methods and Statistical Process Control (SPC). This course is designed for advanced learners with a solid foundation in manufacturing processes and statistical analysis.

Course Coverage

• Evaluating causality of inputs and parameters on output measures
• Designing experiments for process improvement
• Methods for optimizing processes and achieving robustness to noise inputs
• Integration of statistical methods into a comprehensive process control approach
• Developing data-based statistical problem-solving skills for engineering applications
• Capstone activity integrating all Statistical Process Control topics

Who this course is for

• Engineering professionals seeking to advance their careers in manufacturing
• Quality control specialists looking to enhance their process optimization skills
• Manufacturing managers aiming to implement data-driven decision-making processes
• Graduate students in engineering or related fields interested in advanced manufacturing techniques
• Individuals pursuing the Principles of Manufacturing MicroMasters Credential

Real-world Applications

The skills acquired in this course have immediate real-world applications in various industries. Graduates have reported using these concepts daily in their jobs, from driving quality improvements to evaluating process stability. You'll be able to:

1. Implement advanced process control techniques in manufacturing environments
2. Optimize production processes for improved efficiency and quality
3. Design robust manufacturing systems that can withstand external variations
4. Make data-driven decisions to solve complex engineering problems
5. Lead process improvement initiatives in your organization
6. Enhance your company's competitiveness through advanced manufacturing practices

By completing this course, you'll not only gain valuable skills but also position yourself for potential credit towards MIT's Master of Engineering in Advanced Manufacturing & Design program upon earning the MicroMasters Credential.