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

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

doi:10.1557/mrs.2019.157

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

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

Research output: Contribution to journal › Review article › peer-review

73 Scopus citations

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.

Original language	English
Pages (from-to)	545-558
Number of pages	14
Journal	MRS Bulletin
Volume	44
Issue number	7
DOIs	https://doi.org/10.1557/mrs.2019.157
State	Published - Jul 1 2019
Externally published	Yes

Keywords

Coating
Composite
Metal
Optical metallography
Powder metallurgy

Access to Document

10.1557/mrs.2019.157

Cite this

Aggour, K. S., Gupta, V. K., Ruscitto, D., Ajdelsztajn, L., Bian, X., Brosnan, K. H., Chennimalai Kumar, N., Dheeradhada, V., Hanlon, T., Iyer, N., Karandikar, J., Li, P., Moitra, A., Reimann, J., Robinson, D. M., Santamaria-Pang, A., Shen, C., Soare, M. A., Sun, C., ... Vinciquerra, J. (2019). Artificial intelligence/machine learning in manufacturing and inspection: A GE perspective. MRS Bulletin, 44(7), 545-558. https://doi.org/10.1557/mrs.2019.157

@article{1179e5f79e1245289bb78a349a9cd80b,

title = "Artificial intelligence/machine learning in manufacturing and inspection: A GE perspective",

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.",

keywords = "Coating, Composite, Metal, Optical metallography, Powder metallurgy",

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

note = "Publisher Copyright: {\textcopyright} 2019 Materials Research Society.",

year = "2019",

month = jul,

day = "1",

doi = "10.1557/mrs.2019.157",

language = "English",

volume = "44",

pages = "545--558",

journal = "MRS Bulletin",

issn = "0883-7694",

publisher = "Materials Research Society",

number = "7",

}

Aggour, KS, Gupta, VK, Ruscitto, D, Ajdelsztajn, L, Bian, X, Brosnan, KH, Chennimalai Kumar, N, Dheeradhada, V, Hanlon, T, Iyer, N, Karandikar, J, Li, P, Moitra, A, Reimann, J, Robinson, DM, Santamaria-Pang, A, Shen, C, Soare, MA, Sun, C, Suzuki, A, Venkataramana, R & Vinciquerra, J 2019, 'Artificial intelligence/machine learning in manufacturing and inspection: A GE perspective', MRS Bulletin, vol. 44, no. 7, pp. 545-558. https://doi.org/10.1557/mrs.2019.157

TY - JOUR

T1 - Artificial intelligence/machine learning in manufacturing and inspection

T2 - A GE perspective

AU - Aggour, Kareem S.

AU - Gupta, Vipul K.

AU - Ruscitto, Daniel

AU - Ajdelsztajn, Leonardo

AU - Bian, Xiao

AU - Brosnan, Kristen H.

AU - Chennimalai Kumar, Natarajan

AU - Dheeradhada, Voramon

AU - Hanlon, Timothy

AU - Iyer, Naresh

AU - Karandikar, Jaydeep

AU - Li, Peng

AU - Moitra, Abha

AU - Reimann, Johan

AU - Robinson, Dean M.

AU - Santamaria-Pang, Alberto

AU - Shen, Chen

AU - Soare, Monica A.

AU - Sun, Changjie

AU - Suzuki, Akane

AU - Venkataramana, Raju

AU - Vinciquerra, Joseph

PY - 2019/7/1

Y1 - 2019/7/1

N2 - 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.

AB - 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.

KW - Coating

KW - Composite

KW - Metal

KW - Optical metallography

KW - Powder metallurgy

UR - https://www.scopus.com/pages/publications/85072838758

U2 - 10.1557/mrs.2019.157

DO - 10.1557/mrs.2019.157

M3 - Review article

AN - SCOPUS:85072838758

SN - 0883-7694

VL - 44

SP - 545

EP - 558

JO - MRS Bulletin

JF - MRS Bulletin

IS - 7

ER -

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

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this