A.O. Vasyutkin1
1 MIREA – Russian Technological University (Moscow, Russia)

1 vasyutkin.a.o@edu.mirea.ru

Modern systems for designing semiconductor packages and integrated circuits are facing increasingly complex challenges. These challenges often require significant time investments and repeated operations, leading to a need for more efficient and automated solutions.

The goal of the article is to explore the potential of artificial intelligence (AI) techniques, such as multilayer neural networks, generative adversarial networks, reinforcement learning and machine learning, to improve design automation and reduce labor intensity in these processes.

The article explores the potential applications of AI techniques in designing a housing and semiconductor crystal, followed by the as-sembly of a microchip, such as housing matrix editors, component database management systems, graphic legend editors, and circuit board editors. Models corresponding to its tasks have been proposed for each subsystem: multilayer perceptrons for categorization and generative neural networks for optimizing visual representation.

The paper delves into the potential use cases for AI in each of these applications, encompassing automatic object generation, intelligent analysis, and quality control measures.

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