Department of Computer Engineering, Faculty of Computer Science, Universidade da Coruña, 15071 A Coruña, Spain.
Centro de Investigación CITIC, Universidade da Coruña, 15071 A Coruña, Spain.
Sensors (Basel). 2022 Nov 4;22(21):8500. doi: 10.3390/s22218500.
While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.
虽然全球许多公司仍在努力适应工业 4.0 原则,但工业 5.0 的转型已经在进行中。在这种范式下,人机物融合系统(CPHSs)已经出现,利用操作人员的能力来实现复杂制造系统向以人为中心、弹性和可持续性的目标。本文首先描述了开发工业 5.0 CPHS 的基本概念,然后分析了最新的 CPHS,确定了它们的主要设计要求和关键实现组件。此外,还概述了开发此类 CPHS 的主要挑战。接下来,为了说明前面描述的概念,介绍了一个实际的工业 5.0 CPHS。这种 CPHS 能够提高制造过程中操作人员的安全性和操作跟踪,这些制造过程依赖于协作机器人和重型机械。具体来说,所提出的用例包括一个车间,在这个车间中需要更智能地利用资源,并且通过人体接近检测来确定机器何时应该工作或不工作,以避免涉及此类机器的事故或意外。所提出的 CPHS 利用具有智能雾计算节点的混合边缘计算架构来处理热图像,并做出反应以防止工业安全问题。所进行的实验表明,在所选择的实际场景中,所开发的 CPHS 算法能够使用低功率设备(使用 Raspberry Pi 3B)快速准确地检测人体存在(准确率为 97.04%,用时不到 10 毫秒),因此是一种有效的解决方案(例如,在成本、准确性、弹性和计算效率之间进行良好的权衡),可以集成到许多工业 5.0 应用中。最后,本文提供了具体的指导方针,将帮助未来的开发人员和管理人员克服在部署下一代用于智能和可持续制造的 CPHS 时将面临的挑战。