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Artificial intelligence/machine learning in manufacturing and inspection: A GE perspective

  • The Machine Learning Revolution in Materials Research
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Abstract

At GE Research, we are combining “physics” with artificial intelligence and machine learning to advance manufacturing design, processing, and inspection, turning innovative technologies into real products and solutions across our industrial portfolio. This article provides a snapshot of how this physical plus digital transformation is evolving at GE.

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Authors and Affiliations

  1. GE Research, USA

    Kareem S. Aggour, Vipul K. Gupta, Daniel Ruscitto, Leonardo Ajdelsztajn, Xiao Bian, Kristen H. Brosnan, Natarajan Chennimalai Kumar, Voramon Dheeradhada, Timothy Hanlon, Naresh Iyer, Jaydeep Karandikar, Peng Li, Abha Moitra, Johan Reimann, Dean M. Robinson, Alberto Santamaria-Pang, Chen Shen, Monica A. Soare, Changjie Sun, Akane Suzuki, Raju Venkataramana & Joseph Vinciquerra

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  1. Kareem S. Aggour
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  2. Vipul K. Gupta
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  3. Daniel Ruscitto
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  4. Leonardo Ajdelsztajn
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  5. Xiao Bian
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  6. Kristen H. Brosnan
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  7. Natarajan Chennimalai Kumar
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  8. Voramon Dheeradhada
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  9. Timothy Hanlon
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  10. Naresh Iyer
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  11. Jaydeep Karandikar
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  12. Peng Li
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  13. Abha Moitra
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  14. Johan Reimann
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  15. Dean M. Robinson
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  16. Alberto Santamaria-Pang
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  17. Chen Shen
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  18. Monica A. Soare
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  19. Changjie Sun
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  20. Akane Suzuki
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  21. Raju Venkataramana
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  22. Joseph Vinciquerra
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Corresponding author

Correspondence to Kareem S. Aggour.

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Aggour, K.S., Gupta, V.K., Ruscitto, D. et al. Artificial intelligence/machine learning in manufacturing and inspection: A GE perspective. MRS Bulletin 44, 545–558 (2019). https://doi.org/10.1557/mrs.2019.157

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