Large-scale Data Integration for Facilities Analytics: Challenges and Opportunities

被引：2

作者：

Thumati, Balaje T. ^{[1
]}

Subramania, Halasya Siva ^{[1
]}

Shastri, Rajeev ^{[1
]}

Kumar, Karthik Kalyana ^{[1
]}

Hessner, Nicole ^{[1
]}

Villa, Vincent ^{[1
]}

Page, Aaron ^{[1
]}

Followell, David ^{[1
]}

机构：

[1] Boeing Co, Everett, WA 98204 USA

来源：

2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2020年

关键词：

Industry; 4.0; big data; software middleware; data integration; analytics; BIG DATA; SMART; MANAGEMENT;

D O I：

10.1109/BigData50022.2020.9378440

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Industrial Internet of Things (IIoT) is becoming ubiquitous across different industries. However, there are several challenges that needs to be overcome especially in a manufacturing environment which predominantly has legacy hardware and software systems. Further, finding a cost-effective solution becomes crucial when manufacturing facilities are geographically distributed. In this paper, we provide some overview of our complexities across data integration, data analytics, and business impact. Through this knowledge sharing, we address some of the key roadblocks to transform a legacy manufacturing facility into an Industry 4.0 system. All of the findings presented here are based on a two-year pilot project executed at the Boeing Everett site. We believe that digital transformation is must for our future success, but to accomplish this goal at a reasonable cost and effort will be a continued challenge.

引用

页码：3532 / 3538

页数：7

共 11 条

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