US 12,141,230 B2
Process abnormality identification using measurement violation analysis
Selim Nahas, Newton, MA (US); Joseph James Dox, Boxford, MA (US); Vishali Ragam, Chantilly, VA (US); Eric J. Warren, Malta, NY (US); Shijing Wang, Sandy, UT (US); Charles Largo, Saratoga Springs, NY (US); Christopher Reeves, Clifton Park, NY (US); and Randy Raynaldo Corral, Glbert, AZ (US)
Assigned to Applied Materials, Inc., Santa Clara, CA (US)
Filed by Applied Materials, Inc., Santa Clara, CA (US)
Filed on Oct. 31, 2022, as Appl. No. 17/978,075.
Application 17/978,075 is a continuation of application No. 17/163,101, filed on Jan. 29, 2021, granted, now 11,487,848.
Prior Publication US 2023/0052392 A1, Feb. 16, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 17/18 (2006.01); G05B 19/418 (2006.01); H01L 21/67 (2006.01)
CPC G06F 17/18 (2013.01) [G05B 19/41875 (2013.01); H01L 21/67253 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving, by at least one processing device, current metrology data for an operation on a current sample in a fabrication process, the current metrology data comprising a current value for a parameter at each of one or more locations on the current sample;
determining, by the at least one processing device, a current rate of change of the parameter value for each of the one or more locations, the current rate of change of the parameter value associated with the current sample;
identifying, by the at least one processing device, one or more violating locations each having an associated current rate of change of the parameter value that is greater than an associated reference rate of change of the parameter value, wherein the associated reference rate of change is associated with one or more historical rates of change of the parameter value;
identifying, by the at least one processing device, an instance of abnormality of the fabrication process based on the one or more violating locations; and
causing performance of a corrective action associated with fabrication process equipment based on the instance of abnormality.