US 12,298,748 B2
Diagnostic tool to tool matching and full-trace drill-down analysis methods for manufacturing equipment
Sejune Cheon, Seoul (KR); Jeong Jin Hong, Yongin (KR); Mikyung Shim, Seongnam (KR); Xiaoqun Zou, Danville, CA (US); Jinkyeong Lee, Seoul (KR); and Sang Hong Kim, Seoul (KR)
Assigned to Applied Materials, Inc., Santa Clara, CA (US)
Filed by Applied Materials, Inc., Santa Clara, CA (US)
Filed on Jan. 27, 2022, as Appl. No. 17/586,702.
Prior Publication US 2023/0236586 A1, Jul. 27, 2023
Int. Cl. G05B 19/418 (2006.01)
CPC G05B 19/41875 (2013.01) [G05B 2219/32193 (2013.01); G05B 2219/32194 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving trace sensor data associated with a first manufacturing process of a processing chamber;
generating summary data based on the trace sensor data;
generating a quality index score based on the summary data;
in view of the quality index score, processing the trace sensor data using one or more trained machine learning models that generate a representation of the trace sensor data and then generate reconstructed sensor data based on the representation of the trace sensor data, wherein the one or more trained machine learning models output the reconstructed sensor data;
comparing the trace sensor data to the reconstructed sensor data;
determining one or more differences between the reconstructed sensor data and the trace sensor data based on the comparing; and
performing a corrective action associated with the processing chamber based on the one or more differences between the trace sensor data and the reconstructed sensor data, wherein the corrective action comprises one or more of:
scheduling preventative maintenance,
scheduling corrective maintenance, or
updating a process recipe.