Abstract: An apparatus to detect the topology of a workpiece including surface variations and flaws according to images from several viewpoints includes a frame, a loading member, a robot, an image capturing mechanism, and a controller. The loading member is positioned on the frame and loads a workpiece. The controller controls the robot to drive the image capturing mechanism to move or rotate to different preset positions from each of which the image capturing mechanism can capture images of the workpiece and transmit the images to the controller. The controller further processes the images to obtain an assessment of the components and surface of the workpiece for further processing.

Abstract: A smart decision feedback method for inspecting a circuit board includes obtaining a number of abnormal solder paste points of a circuit board identified by a solder paste inspection device, determining whether the number of abnormal solder paste points is greater than or equal to a first predetermined value, determining whether an identification result of the solder paste inspection device is abnormal when the number of abnormal solder paste points is less than the first predetermined value, obtaining an inspection result performed by a testing device inspecting the circuit board when the identification result of the solder paste inspection device is abnormal, analyzing an adjustment parameter of the solder paste inspection device, and sending the adjustment parameter to the solder paste inspection device. A first prompt is displayed when the number of abnormal solder paste points is greater than or equal to the first predetermined value.

Abstract: A machine learning method is used for improving accuracy of an automated optical inspection (AOI) device. The method includes obtaining an image of a component to be inspected, processing the image to generate digital image information, establishing a machine learning model according to the digital image information, inputting the digital image information into the machine learning model for determination, verifying accuracy of a result of determination by the machine learning model, adjusting and optimizing the machine learning model according to the result of determination of the accuracy of the machine learning model, and improving the machine learning model until the machine learning model reaches a predetermined accuracy.

Abstract: An apparatus to detect the topology of a workpiece including surface variations and flaws according to images from several viewpoints includes a frame, a loading member, a robot, an image capturing mechanism, and a controller. The loading member is positioned on the frame and loads a workpiece. The controller controls the robot to drive the image capturing mechanism to move or rotate to different preset positions from each of which the image capturing mechanism can capture images of the workpiece and transmit the images to the controller. The controller further processes the images to obtain an assessment of the components and surface of the workpiece for further processing.