High-Performance Computing Based Big Data Analytics for Smart Manufacturing

Author:

Yang Yuhang1,Cai Y. Dora1,Lu Qiyue1,Zhang Yifang1,Koric Seid1,Shao Chenhui1

Affiliation:

1. University of Illinois at Urbana-Champaign, Urbana, IL

Abstract

With the rapid development of sensing, communication, and computing technologies and infrastructure, today’s manufacturing industry is marching towards a big data era and a new generation of digitalization and intelligence. The availability of big data provides us with a golden opportunity to promote smart manufacturing. Nevertheless, the deployment and popularization of big data analytics in manufacturing is still at its nascent stage. One critical challenge results from the lack of high-performance computing (HPC) capability, which is crucial for responsive and intelligent decision-making in the modern manufacturing industry. To address this challenge, this paper proposes a framework and some general guidelines for implementing big data analytics in an HPC environment. The details of the whole workflow, from the prototype to the final application, are high-lighted. A case study for intelligent 3D sensing with real-world manufacturing data is presented to demonstrate the effectiveness of the proposed framework.

Publisher

American Society of Mechanical Engineers

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Infrastructure Analysis: A Turning Point for the Adoption of Industry 4.0 Technologies;Proceedings of the 11th International Conference on Production Research – Americas;2023

2. Evaluation of product conceptual design based on Pythagorean fuzzy set under big data environment;Scientific Reports;2022-12-27

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