Research on the Application of Artificial Intelligence Technology in Microelectronics Testing and Fault Diagnosis

This paper explores the integration of Artificial Intelligence (AI) technologies in the field of microelectronics testing and troubleshooting. Traditional methods for testing and troubleshooting microelectronic devices often face challenges such as high complexity, time-consumption, and the need for expert intervention. AI technologies, with their advanced capabilities in machine learning, neural networks, and expert systems, offer promising solutions to these problems. This study provides an overview of the key AI approaches employed in microelectronics, discusses their implementation in various test and diagnostic scenarios, and evaluates their impact in terms of improved accuracy, efficiency, and automation. Through a detailed analysis of case studies and real-world applications, the paper demonstrates how AI-driven approaches are revolutionizing the microelectronics industry, paving the way for more reliable and sophisticated electronic devices. The study concludes with a discussion of the current limitations of AI technologies in the field and suggests potential directions for future research and development.