Intelligent Fault Analysis Decision Flow in Semiconductor Industry 4.0 Using Natural Language Processing with Deep Clustering

Autor: Kenneth Ezukwoke, Houari Toubakh, Xavier Boucher, Pascal Gounet, Mireille Batton-Hubert, Anis Hoayek

Publikováno v: IEEE 17th International Conference on Automation Science and Engineering (CASE)
IEEE 17th International Conference on Automation Science and Engineering (CASE), Aug 2021, Lyon, France. p 429-436
CASE

International audience; Microelectronics production failure analysis is a time-consuming and complicated task involving successive steps of analysis of complex process chains. The analysis is triggered to find the root cause of a failure and its find

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::032cfcda7a65e7fb8ecaeefbecd04718
https://hal-emse.ccsd.cnrs.fr/emse-03325358

Unsupervised approach for an optimal representation of the latent space of a failure analysis dataset.

Autor: Rammal, Abbas¹ (AUTHOR) rammal_abbass@hotmail.com, Ezukwoke, Kenneth¹ (AUTHOR), Hoayek, Anis¹ (AUTHOR), Batton-Hubert, Mireille¹ (AUTHOR)

Publikováno v: Journal of Supercomputing. Mar2024, Vol. 80 Issue 5, p5923-5949. 27p.

Natural language processing (NLP) and association rules (AR)-based knowledge extraction for intelligent fault analysis: a case study in semiconductor industry.

Autor: Wang, Zhiqiang¹ (AUTHOR) zhiqiang.wang@devinci.fr, Ezukwoke, Kenneth^2,3 (AUTHOR), Hoayek, Anis^2,3 (AUTHOR), Batton-Hubert, Mireille^2,3 (AUTHOR), Boucher, Xavier^2,4 (AUTHOR)

Publikováno v: Journal of Intelligent Manufacturing. Nov2023, p1-16.