Industrial Internet of Things Intelligence Empowering Smart
Manufacturing: A Literature Review
- URL: http://arxiv.org/abs/2312.16174v2
- Date: Thu, 22 Feb 2024 02:28:57 GMT
- Title: Industrial Internet of Things Intelligence Empowering Smart
Manufacturing: A Literature Review
- Authors: Yujiao Hu, Qingmin Jia, Yuao Yao, Yong Lee, Mengjie Lee, Chenyi Wang,
Xiaomao Zhou, Renchao Xie, F. Richard Yu
- Abstract summary: This paper provides a comprehensive overview of IIoT intelligence.
We first conduct an in-depth analysis of the inevitability of manufacturing transformation.
Then we show the value of IIoT intelligence for industries in fucntions, operations, deployments, and application.
- Score: 24.773086605569596
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The fiercely competitive business environment and increasingly personalized
customization needs are driving the digital transformation and upgrading of the
manufacturing industry. IIoT intelligence, which can provide innovative and
efficient solutions for various aspects of the manufacturing value chain,
illuminates the path of transformation for the manufacturing industry. It's
time to provide a systematic vision of IIoT intelligence. However, existing
surveys often focus on specific areas of IIoT intelligence, leading researchers
and readers to have biases in their understanding of IIoT intelligence, that
is, believing that research in one direction is the most important for the
development of IIoT intelligence, while ignoring contributions from other
directions. Therefore, this paper provides a comprehensive overview of IIoT
intelligence. We first conduct an in-depth analysis of the inevitability of
manufacturing transformation and study the successful experiences from the
practices of Chinese enterprises. Then we give our definition of IIoT
intelligence and demonstrate the value of IIoT intelligence for industries in
fucntions, operations, deployments, and application. Afterwards, we propose a
hierarchical development architecture for IIoT intelligence, which consists of
five layers. The practical values of technical upgrades at each layer are
illustrated by a close look on lighthouse factories. Following that, we
identify seven kinds of technologies that accelerate the transformation of
manufacturing, and clarify their contributions. The ethical implications and
environmental impacts of adopting IIoT intelligence in manufacturing are
analyzed as well. Finally, we explore the open challenges and development
trends from four aspects to inspire future researches.
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