Systems and methods for predicting a quality of a printed circuit board assembly

An apparatus comprising:

• a processor;
• and
• a memory,
• wherein the processor is configured to:
• obtain production data relating to production of a PCB assembly, the production data including solder paste information;
• map the production data, including the solder paste information, onto a latent vector of a latent space of a trained adaptive algorithm, wherein the trained adaptive algorithm is trained on real X-ray images of PCB assemblies, serves for generating X-ray images of the PCB assemblies, or a combination thereof, and
• determine a subspace of the latent space related to the latent vector, the subspace indicating a quality of the PCB assembly;
• generate, by the trained adaptive algorithm, based on the latent vector, an X-ray image of the PCB assembly, such that a quality of the PCB assembly is determined;
• or
• a combination thereof,
• wherein the solder paste information includes a formation, a size, and a volume of one or more solder depots applied to the PCB assembly,
• wherein the PCB assembly comprises a plurality of regions of interest, each region of interest of the plurality of regions of interest comprising one or more soldering points, the respective region of interest corresponding to an area of the PCB assembly, an area of an image of the PCB assembly, or the area of the PCB assembly and the area of the image of the PCB assembly, the production data relating to the respective region of interest, and
• wherein the processor is further configured to select, for each region of interest of the plurality of regions of interest, a corresponding trained adaptive algorithm for determining the quality of the PCB assembly, and
• wherein the plurality of regions of interest differ regarding a number of the one or more soldering points, positions of the one or more soldering points, sizes of the one or more soldering points, or any combination thereof.

A computer-implemented method of obtaining an adaptive algorithm for predicting a quality of one or more printed circuit board (PCB) assemblies, the computer-implemented method comprising:

• obtaining real X-ray images of one or more PCB assemblies;
• training an autoencoder capable of reconstructing the real X-ray images input;
• obtaining the adaptive algorithm for predicting the quality of the one or more PCB assemblies, the obtaining of the adaptive algorithm comprising identifying a decoder part of the autoencoder,
• wherein the decoder part serves as a latent space interpreter,
• wherein the adaptive algorithm is configured to receive a latent space vector as input and reconstruct or generate an X-ray image based on the received latent space vector as output, the latent space vector being based on production data,
• wherein the production data includes solder paste information, the solder paste information including a formation, a size, and a volume of one or more solder depots applied to the one or more PCB assemblies,
• wherein a PCB assembly of the one or more PCB assemblies comprises a plurality of regions of interest, each region of interest of the plurality of regions of interest comprising one or more soldering points, the respective region of interest corresponding to an area of the PCB assembly, an area of an image of the PCB assembly, or the area of the PCB assembly and the area of the image of the PCB assembly, the production data relating to the respective region of interest,
• wherein the computer-implemented method further comprises selecting, for each region of interest of the plurality of regions of interest, a corresponding trained adaptive algorithm for determining the quality of the PCB assembly, and
• wherein the plurality of regions of interest differ regarding a number of the one or more soldering points, positions of the one or more soldering points, sizes of the one or more soldering points, or any combination thereof.