Fall | Graduate | 12 Units | Prereq: 2.008, 6.041, or 6.152
Statistical modeling and control in manufacturing processes. Use of experimental design and response surface modeling to understand manufacturing process physics. Defect and parametric yield modeling and optimization. Forms of process control, including statistical process control, run by run and adaptive control, and real-time feedback control. Application contexts include semiconductor manufacturing, conventional metal and polymer processing, and emerging micro-nano manufacturing processes.
Fall 2020 Update: Fully Remote Classes - We will use a "flipped classroom" format as was done in the Fall of 2019. All lectures will be asynchronous using the existing MITx material (2.830.1x and 2.830.2x), and we will meet (using Zoom) during normal class time for discussion, extended examples, case studies and class challenges. The group project at the end will proceed as normal, but done virtually in teams of 3-4.