PRINTED CIRCUIT BOARD INSPECTING APPARATUS, METHOD FOR DETECTING ANOMALY IN SOLDER PASTE AND COMPUTER READABLE RECORDING MEDIUM
FIG2 is a flowchart of a method of detecting whether an anomaly in solder pastes printed on a printed circuit board occurred, according to various embodiments of the present disclosure
FIG2 is a flowchart of a method of detecting whether an anomaly in solder pastes printed on a printed circuit board occurred, according to various embodiments of the present disclosure. Process steps, method steps, and algorithms are sequentially illustrated in the flowcharts of FIG2, 6, 7, 8 and 9 but the processes, methods, and algorithms may be performed in a predetermined sequence as appropriate. In other words, the steps of processes, methods, and algorithms described in various embodiments of the present disclosure are not necessarily performed in the sequence described herein. Further, although some steps are described as being non-simultaneously performed, they may be simultaneously performed in another embodiment. Further, examples of processes shown in the drawings do not mean that the exemplary processes exclude other changes and modifications, do not mean that some of the exemplary processes or the steps of the processes are necessary in one of various embodiments of the present disclosure, and do not mean that the exemplary processes are preferable.
flowchart
210
230
described below. In step may perform steps
130
processor
100
220
In step may perform steps
2
following Equation
101
screen printer
110
image sensor
120
memory
['1. A printed circuit board inspection apparatus (100),  characterized by a memory (120) configured to store a machine-learning based model (320, 420) configured to derive a probability value that each of two solder pastes has measurement shape information when the two solder pastes are printed on a printed circuit board through two apertures having a predetermined aperture shape, which are formed in a stencil, using aperture shape information of the two apertures and the measurement shape information about each of the two solder pastes; an image sensor (110) configured to obtain an image (340) of a first printed circuit board; and a processor (130) electrically connected with the memory (120), wherein the processor (130) is configured to: obtain, from the image (340) of the first printed circuit board obtained by the image sensor (110), measurement shape information about each of a plurality of solder pastes printed on the first printed circuit board through a plurality of apertures formed in the stencil, obtain aperture shape information about each of the plurality of apertures, obtain probability values that a first solder paste printed through a first aperture of the plurality of apertures and each of a plurality of second solder pastes printed through second apertures other than the first aperture of the plurality of apertures have the measurement shape information when the first solder paste and the plurality of second solder pastes are printed on the first printed circuit board, by applying the obtained measurement shape information and the obtained aperture shape information to the machine-learning based model (320, 420), and detect whether an anomaly in the first solder paste occurred based on the obtained probability values.']