Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Neerja Bawaskar"'
Autor:
Neerja Bawaskar, Fadi Batarseh, Davide Pacifico, Atul Chittora, Shenghua Song, Monisa Ramesh Babu, Shobhit Malik, Janam Bakshi
Publikováno v:
International Symposium for Testing and Failure Analysis.
Many fabless customers do not share the design information such as LEF/DEF (Library Exchange Format and Design Exchange Format), design netlist, and test program information with foundries because they contain proprietary IP. Determining the root-cau
Autor:
Sudhakar M. Reddy, Gaurav Veda, Yue Tian, Neerja Bawaskar, Huaxing Tang, Manish Sharma, Wu-Tung Cheng
Publikováno v:
ETS
Volume diagnosis has been used effectively to identify systematic defects for yield learning. Root cause deconvolution (RCD), an unsupervised machine learning technique which uses volume diagnosis data, has proven very effective for identifying root
Autor:
Zhigang Song, Tarl Gordon, Teng-Yin Lin, Kan Zhang, Neerja Bawaskar, Steve Crown, Yandong Liu, Martin O'tool, Kannan Sekar, Toni Laaksonen, Daniel Greenslit, Mark Lagus, Ishtiaq Ahsan, Bill Evans, Joerg Winkler, Shahrukh Khan, DK Sohn, Frank Barth, John Masnik
Publikováno v:
2019 30th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC).
Functional logic test structures with ATPG blocks and scan chains have been the traditional inline logic learning vehicle for technology learning and development. However, these test structures often need processing of wafers up to a higher BEOL proc
Autor:
Kannan Sekar, Neerja Bawaskar, Huaxing Tang, Matt Knowles, Gaurav Veda, Wu-Tung Cheng, Manish Sharma, Douglas Gehringer, Yan Pan, Jayant D'Souza
Publikováno v:
2019 30th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC).
Device complexity is reaching all-time highs with the adoption of high aspect ratio FinFETs created using multi- patterning process technologies. Simultaneously, new product segments such as AI and automotive are being fabricated on such advanced pro
Autor:
Atul Chittora, John Carulli, Yan Pan, Sherwin Fernandes, Rao Desineni, Neerja Bawaskar, Kannan Sekar
Publikováno v:
ITC
This paper describes a volume diagnosis infrastructure built on open-source software, which addresses practical challenges in a foundry environment by integrating various data sources from design, manufacturing process and test to enable rapid root-c