Learn how to model variations in manufacturing processes and develop methods to reduce and control deterministic variations to achieve consistent process quality.
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 will you 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