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 |
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| Přispěvatelé: | École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne-Institut Henri Fayol, Département Génie de l’environnement et des organisations (FAYOL-ENSMSE), Institut Henri Fayol-Ecole Nationale Supérieure des Mines de St Etienne, STMicroelectronics, Breuil, Florent, Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, Institut Henri Fayol-Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Failure analysis
Computer science 030204 cardiovascular system & hematology computer.software_genre 03 medical and health sciences 0302 clinical medicine Artificial Intelligence Machine learning 030212 general & internal medicine Cluster analysis business.industry Deep learning Natural language processing Root cause Mixture model Industry 4.0 Automation Autoencoder [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation Artificial intelligence [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation business computer Natural language Decision analysis |
| Zdroj: | 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 |
| Popis: | 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 findings, recorded in a reporting system using natural language. Fault analysis, physical analysis, sample preparation and package construction analysis are arguably the most used analysis activity for determining the root-cause of a failure. Intelligent automation of this analysis decision process using artificial intelligence is the objective of the FA 4.0 consortium; creating a reliable and efficient semiconductor industry. This research presents natural language processing (NLP) techniques to find a coherent representation of the expert decisions during fault analysis. The adopted methodology is a Deep learning algorithm based on β-variational autoencoder (β-VAE) for latent space disentanglement and Gaussian Mixture Model for clustering of the latent space for class identification. |
| Databáze: | OpenAIRE |
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