Vorhersage der Qualität einer Leiterplattenanordnung anhand von Produktionsdaten

Details

Veröffentlichungs-Nr.

EP4138032

Aktenzeichen

EP21191727

Anmeldetag

17. August 2021

Veröffentlichung

22. Februar 2023

Rechtsraum

EP

IPC

G06T7/00

Abstract

A computer-implemented method of predicting a quality of a printed circuit board, PCB, assembly (1) comprising the steps of: Obtaining (S0) production data (101) relating to the production (100) of the PCB assembly (1), Mapping (S1), preferably based on a trained regression algorithm (102), the production data onto a latent vector (103) of a latent space of a trained adaptive algorithm (104), wherein the trained adaptive algorithm (104) is trained on real X-ray images (20) of PCB assemblies and/or serves for generating X-ray images (105) of PCB assemblies, and Determining (S2) a subspace (106) of the latent space related to the latent vector (103), the subspace (106) indicating a quality (107) of the PCB assembly (1), in particular of a region of interest (R1) of the PCB assembly (1), and/or Generating (S3), by the trained adaptive algorithm (104), based on the latent vector (103), an X-ray image (105) of the PCB assembly (1), in particular of the region of interest (R1), in order to determine a quality (107) of the PCB assembly (1).

Anmelder

Firmen

Siemens Aktiengesellschaft
Friedrich-Alexander-Universität Erlangen-Nürnberg

Land

🇩🇪 Deutschland

Fachgebiete