Enterprise Integration and Interoperability for Big Data-Driven Processes in the Frame of Industry 4.0

被引:7
|
作者
Bousdekis, Alexandros [1 ]
Mentzas, Gregoris [1 ]
机构
[1] Natl Tech Univ Athens NTUA, Informat Management Unit IMU, Sch Elect & Comp Engn, Athens, Greece
来源
FRONTIERS IN BIG DATA | 2021年 / 4卷
关键词
conceptual modeling; data analytics; enterprise architecture; data management; smart manufacturing; predictive maintenance; DECISION-MAKING; SYSTEMS; ARCHITECTURES; SOFTWARE; CONTEXT; DESIGN; MODEL; IOT;
D O I
10.3389/fdata.2021.644651
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traditional manufacturing businesses lack the standards, skills, processes, and technologies to meet today's challenges of Industry 4.0 driven by an interconnected world. Enterprise Integration and Interoperability can ensure efficient communication among various services driven by big data. However, the data management challenges affect not only the technical implementation of software solutions but the function of the whole organization. In this paper, we bring together Enterprise Integration and Interoperability, Big Data Processing, and Industry 4.0 in order to identify synergies that have the potential to enable the so-called "Fourth Industrial Revolution." On this basis, we propose an architectural framework for designing and modeling Industry 4.0 solutions for big data-driven manufacturing operations. We demonstrate the applicability of the proposed framework through its instantiation to predictive maintenance, a manufacturing function that increasingly concerns manufacturers due to the high costs, safety issues, and complexity of its application.
引用
收藏
页数:18
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