公开(公告)号：US20240273278A1

公开(公告)日：2024-08-15

申请号：US18568115

申请日：2022-06-07

Applicant: ASML NETHERLANDS B.V.

Inventor： Pieter VAN HERTUM ,  Dimitra GKOROU ,  Joachim Kinley VAN SCHOUBROECK ,  Zahra KAREVAN ,  Alexander YPMA

IPC: G06F30/398 ,  G03F7/00

CPC classification number: G06F30/398 ,  G03F7/705 ,  G03F7/70508

Abstract: A computer implemented method for diagnosing a system includes: receiving a causal graph, the causal graph defining (i) a plurality of nodes each representing a module of a plurality of modules of a system, wherein each module is characterized by one or more signals; and (ii) edges connected between the nodes, the edges representing propagation of performance between modules; generating a reasoning tool by augmenting the causal graph with diagnostics knowledge based on historically determined relations between performance, statistical and causal characteristics of at least one module out of the plurality of modules; obtaining a health metric of the at least one module, wherein the health metric is associated with the one or more signals associated with the at least one module; and using the health metric as an input to the reasoning tool to identify a module that is the most likely cause of the behavior.

公开(公告)号：US20250029014A1

公开(公告)日：2025-01-23

申请号：US18712765

申请日：2022-11-21

Applicant: ASML NETHERLANDS B.V.

Inventor： Dimitriy DOUNAEV ,  Dimitra GKOROU ,  Zahra KAREVAN ,  Jefrey LIJFFIJT ,  Pieter VAN HERTUM ,  Joachim Kinley VAN SCHOUBROECK ,  Alexander YPMA

IPC: G06N20/20 ,  G03F7/00

Abstract: A fault in a subject production apparatus which is suspected of being a deviating machine, is identified based on whether it is possible to train a machine learning model to distinguish between first sensor data derived from the subject production apparatus, and second sensor data derived from one or more other production apparatuses which are assumed to be behaving normally. Thus, the discriminative ability of the machine learning model is used as an indicator to discriminate between a faulty machine and the population of healthy machines.