公开(公告)号：US20220082949A1

公开(公告)日：2022-03-17

申请号：US17423325

申请日：2020-01-09

Applicant: ASML NETHERLANDS B.V.

Inventor： Arnaud HUBAUX ,  Johan Franciscus Maria BECKERS ,  Dylan John David DAVIES ,  Johan Gertrudis Cornelis KUNNEN ,  Willem Richard PONGERS ,  Ajinkya Ravindra DAWARE ,  Chung-Hsun LI ,  Georgios TSIROGIANNIS ,  Hendrik Cornelis Anton BORGER ,  Frederik Eduard DEJONG ,  Juan Manuel GONZALEZ HUESCA ,  Andriy HLOD ,  Maxim PISARENCO

IPC: G03F7/20 ,  G03F1/70 ,  G06F30/392

Abstract: A method for categorizing a substrate subject to a semiconductor manufacturing process including multiple operations, the method including: obtaining values of functional indicators derived from data generated during one or more of the multiple operations on the substrate, the functional indicators characterizing at least one operation; applying a decision model including one or more threshold values to the values of the functional indicators to obtain one or more categorical indicators; and assigning a category to the substrate based on the one or more categorical indicators.

公开(公告)号：US20170363969A1

公开(公告)日：2017-12-21

申请号：US15527645

申请日：2015-09-21

Applicant: ASML NETHERLANDS B.V.

Inventor： Marc HAUPTMANN ,  Dylan John David DAVIES ,  Paul JANSSEN ,  Naoko TSUGAMA ,  Richard Joseph BRULS ,  Kornelis Tijmen HOEKERD ,  Edwin Johannes Maria JANSSEN ,  Petrus Johannes VAN DEN OEVER ,  Ronald VAN DER WILK ,  Antonius Hubertus VAN SCHIJNDEL ,  Jorge Alberto VIEYRA SALAS

IPC: G03F7/20 ,  G01N27/61

CPC classification number: G03F7/70616 ,  G01N21/9501 ,  G01N27/61 ,  G01N2021/95676 ,  G03F1/84 ,  G03F7/70508 ,  G03F7/70783 ,  H01L22/12 ,  H01L22/20

Abstract: A diagnostic apparatus monitors a lithographic manufacturing system. First measurement data representing local deviations of some characteristic across a substrate is obtained using sensors within a lithographic apparatus, and/or a separate metrology tool. Other inspection tools perform substrate backside inspection to produce second measurement data. A high-resolution backside defect image is processed into a form in which it can be compared with lower resolution information from the first measurement data. Cross-correlation is performed to identify which of the observed defects are correlated spatially with the deviations represented in the first measurement data. A correlation map is used to identify potentially relevant clusters of defects in the more detailed original defect map. The responsible apparatus can be identified by pattern recognition as part of an automated root cause analysis. Alternatively, reticle inspection data may be used as second measurement data.