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The main problem of introducing technical vision systems is their integration into numerical control systems of installations in order to increase the speed of technological operations. Thus, the development of real-time algorithms that determine the position of semiconductor crystals relative to the substrate, their implementation in the form of programs for specialized controllers integrated directly into CNC systems, is an urgent task.
The paper presents the implementation of a system for adjusting the position of a semiconductor crystal or microcircuit by processing a video stream from high-resolution cameras, which determines the true coordinates, position relative to the reference marks of the substrate and heating table, and outputs them directly to the CNC programmable logic controller. system. The basis of the system is the 64-bit RISC-V core.
One of the problems of machine that arises when carrying loads, is the impact of factors, such as pendulum fluctuations of the load, compression of suspension cables. In conventional manipulators, such as cranes, this is determined by the skill of the operator. This is not possible in fully controlled non-orthogonal manipulators with multiple actuators.
To solve these problems, the authors of the article use two stereo cameras, the data from which, through mathematical transformations, is fed into the control system. Using a stereo camera is the simplest way to go from object coordinates in pixels an image, in an actual offset expressed in units of length.
The authors of the article eliminated this drawback by using two non-orthogonally located cameras, the focuses of which coincide with the location of the crystal on the working tool. The resulting two images are then processed. The contours of the reference marks on the substrate, already installed elements and the mounted crystal are highlighted. After geometric transformations of the selected contours, the operator receives a real-time map of elements and can adjust the position of the chip in the horizontal plane. All operations are performed in real time. This approach has been practically tested on industrial equipment developed with the direct participation of the authors.
The effectiveness test was carried out on a set of test images obtained by the flip chip machine, images by a microcircuit analyzer, as well as data from the product production line. The analyzation frames had low resolution and poor lighting. Images are captured in RGB color space.
The research described in this article demonstrates the significant potential for automation and optimization in the context of microchip analysis processes. Automated analysis systems can eliminate the need for manual labor, leading to increased efficiency, accuracy, and consistency.
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