Artificial intelligence excels in image processing by reliably recognizing defect features, even when the image data contains significant interference factors. For instance, shadows in X-ray images can complicate automatic inspection using traditional methods. However, AI effectively detects these issues. The processed results are then available for established inspection algorithms to further analyze in the inspection plan.
Depending on the application, AI can reduce inspection times and increase First Pass Yield (FPY). Artificial intelligence is also capable of replacing complex inspection strategies. Where manual or semi-automatic methods once led to optimal results, AI now offers an alternative approach, making it possible to quickly and successfully tackle previously unsolved tasks with AI supported image processing.
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High temperatures are expected in electronic components, especially in power electronics. Hidden gas inclusions in planar solder joints can lead to overheating and component failure. Nowadays, with 3D X-ray images and layer images, these voids can be inspected and measured without error. AI is paving the way for new possibilities to achieve equivalent results in 2D, saving cycle time.
The applications of AI supported image processing are diverse, and the added value is quickly evident when inspecting BGA components. Detecting BGA balls or voids in BGA balls can deliver more stable results with this advanced method. Approaches from pCT and artificial intelligence can be combined here.
Input and Output Image
Input and Output Image
Input and Output Image
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Quality control has long been a standard in electronics production, and with the growing complexity of components and resulting criteria, it has become an essential process step. Effective inspection relies on proven concepts and methods, such as robust algorithms, precise 3D measurement techniques, and high-resolution image processing. Building on these foundations, we offer additional AI-powered tools for our inspection systems.
In automated quality assurance, the distinction between "acceptable component" and "defective component" can be so fine that the results need to be reclassified. Viscom's AI based verification leverages deep learning to assist production sites. Following the four-eyes principle, the AI's results are compared with the operator's decisions. If there's a deviation, a notification prompts for correction or confirmation of the input, preventing misclassification early on. Transitioning smoothly to autonomous classification, the AI can make independent decisions in predefined areas, significantly reducing time.
Meet vAI ProVision, Viscom’s groundbreaking AI-powered inspection software that transforms how 3D AOI inspection programs are created. By embedding advanced artificial intelligence directly into Viscom’s vVision Software, inspection programs can now be automatically generated and optimized in minutes: faster, smarter, and more efficiently than ever before.
