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Practical applications of AI in test operations: efficient, predictive burn-in avoidance

Thursday, September 19
11:05am to 11:30am

Abstract:
 
As the semiconductor industry adopts more aspects of Industry 4.0, one area that continues to generate a lot of interest is the use of artificial intelligence and machine learning to improve manufacturing test operations. Virtually every company has “sandbox” projects where AI and ML algorithms are used on controlled sets of data with some degree of success. But when those same algorithms are deployed into actual production environments, the fluid nature of high-volume production reveals the real-world challenges when trying to make AI and ML applications truly autonomous. This presentation will discuss what is needed to make AI and ML algorithms “production-ready” and will showcase a real-world example of using ML to perform “virtual” burn-in in lieu of traditional burn-in, dramatically reducing overall test costs and with zero impact on product quality and reliability.
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