An Autoencoder-Based Approach for Fault Detection in Multi-Stage Manufacturing: A Sputter Deposition and Rapid Thermal Processing Case Study-Reference-Cited by-同舟云学术

An Autoencoder-Based Approach for Fault Detection in Multi-Stage Manufacturing: A Sputter Deposition and Rapid Thermal Processing Case Study

Author:

Jebril Hana T. T.¹^ORCID,Pleschberger Martin²^ORCID,Susto Gian Antonio³^ORCID

Affiliation:

1. Christian Doppler Lab for Artificial Intelligence in Retina, Medical University of Vienna, Vienna, Austria

2. DSC Department, Kompetenzzentrum Automobil- und Industrieelektronik GmbH, Villach, Austria

3. Department of Information Engineering, University of Padova, Padua, Italy

Funder

Electronic Components and Systems for European Leadership Joint Undertaking (JU) through the EU Project iDev40

The JU receives support from the European Union’s Horizon 2020 Research and Innovation Programme and Austria

Germany, Belgium, Italy, Spain, Romania

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Link

Reference28 articles.

5. What do we understand about convolutional networks?;hadji;arXiv 1803 08834,2018

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