Introduction to Wafer Tomography: Likelihood-Based Prediction of Integrated-Circuit Yield

Michael Baron (), Emmanuel Yashchin () and Asya Takken ()
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Michael Baron: American University
Emmanuel Yashchin: IBM Research Division
Asya Takken: Alliant Cooperative Data

A chapter in Artificial Intelligence, Big Data and Data Science in Statistics, 2022, pp 227-252 from Springer

Abstract: Abstract A concept of wafer tomography is introduced referring to a detailed reconstruction of hidden information on integrated circuits given incomplete and sparse layer-by-layer data that are usually available. Proposed tools associate chip failures with all observed, partially observed, and unobserved defects on a chip via a cause-and-effect relationship to predict the final yield at any time during the production process. The method also allows to determine the most probable causes of failures, the most dangerous defects, the most vulnerable layers, the most influential factors, and their combinations.

Keywords: Diagnostics; EM algorithm; Kill ratio; Tomography; Wafer inspection; Yield prediction (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-07155-3_9

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DOI: 10.1007/978-3-031-07155-3_9

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