[论文解读] Industrial Internet of Things Intelligence Empowering Smart Manufacturing: A Literature Review

Yujiao Hu, Qingmin Jia+7 more|arXiv (Cornell University)|Dec 2, 2023

Digital Transformation in Industry被引用 8

一句话总结

简要直接回答：一篇全面的文献综述，界定了工业物联网（IIoT）智能，提出五层层次架构，并确定推动智能制造转型的七项技术。

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.

研究动机与目标

• 解释制造业转型的必然性并从中国行业实践中提取可行经验教训。
• 定义IIoT智能并阐述其在制造功能、运营、部署和应用中的价值。
• 提出用于IIoT智能的分层开发架构，并通过标杆工厂洞见说明其收益。
• 识别七种技术，阐明其在加速IIoT智能中的作用。
• 讨论开放挑战与未来趋势，以引导未来研究。

提出的方法

• 将IIoT智能定义为覆盖整个价值链的技术、方法、生产与平台。
• 提出五层分层开发架构：设备、网络、软件、建模、分析与优化。
• 以标杆工厂案例说明各层的实际价值。
• 识别七类技术并描述它们在加速IIoT智能中的作用。
• 综合数字化控制、确定性响应、成本友好部署与普及等方面的开放挑战和未来趋势。

实验结果

研究问题

• RQ1 IIoT智能是什么，它能为智能制造带来什么？
• RQ2 IIoT智能的开发架构是什么？
• RQ3 哪些技术能加速IIoT智能的发展？
• RQ4 IIoT智能的开放挑战与未来趋势是什么？

主要发现

• IIoT智能实现制造价值链的数字连接、感知、智能分析、认知和实时决策。
• 五层分层架构（设备、网络、软件、建模、分析与优化）清晰地阐明了IIoT智能如何驱动智能制造。
• 七项技术加速IIoT智能：工业机器人、机器视觉、网络、数字孪生、深度学习、智能硬件、云/边缘计算。
• 标杆工厂展示了架构各层升级的实际价值和回报。
• 在数字化控制、确定性响应、部署成本以及IIoT智能的普及方面识别出开放挑战与未来趋势。