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

被引：40

作者：

Aggour, Kareem S. ^{[1
]}

Gupta, Vipul K. ^{[2
]}

Ruscitto, Daniel ^{[3
]}

Ajdelsztajn, Leonardo ^{[2
]}

Bian, Xiao ^{[4
]}

Brosnan, Kristen H. ^{[2
]}

Kumar, Natarajan Chennimalai ^{[5
]}

Dheeradhada, Voramon ^{[2
]}

Hanlon, Timothy ^{[2
]}

Iyer, Naresh ^{[6
]}

Karandikar, Jaydeep ^{[7
]}

Li, Peng ^{[7
]}

Moitra, Abha ^{[1
]}

Reimann, Johan ^{[6
]}

Robinson, Dean M. ^{[8
]}

Santamaria-Pang, Alberto ^{[4
]}

Shen, Chen ^{[2
]}

Soare, Monica A. ^{[2
]}

Sun, Changjie ^{[5
]}

Suzuki, Akane ^{[2
]}

Venkataramana, Raju ^{[9
]}

Vinciguerra, Joseph ^{[10
]}

机构：

[1] GE Res, AI Knowledge & Big Data Grp, Niskayuna, NY 12309 USA

[2] GE Res, Struct Mat Grp, Niskayuna, NY USA

[3] GE Res, Mat Characterizat Grp, Niskayuna, NY USA

[4] GE Res, AI & Comp Vis Grp, Niskayuna, NY USA

[5] GE Res, Mech & Design Grp, Niskayuna, NY USA

[6] GE Res, AI & Machine Learning Grp, Niskayuna, NY USA

[7] GE Res, Struct Mat Mfg Grp, Niskayuna, NY USA

[8] GE Res, Addit Mfg Technol Grp, Niskayuna, NY USA

[9] GE Res, Human Comp Interact Grp, Niskayuna, NY USA

[10] GE Res, Addit Platform, Niskayuna, NY USA

来源：

MRS BULLETIN | 2019年 / 44卷 / 07期

关键词：

composite; metal; coating; powder metallurgy; optical metallography; PREDICTION; MODELS; LIFE;

D O I：

10.1557/mrs.2019.157

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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. © 2019 Materials Research Society.

引用

页码：545 / 558

页数：14

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