| Title |
Intelligent Collaborative Manufacturing Space for Augmenting Human Workers in Semi-Automated Manufacturing Systems |
| ID_Doc |
68313 |
| Authors |
Ruppert, T; Locklin, A; Romero, D; Abonyi, J |
| Title |
Intelligent Collaborative Manufacturing Space for Augmenting Human Workers in Semi-Automated Manufacturing Systems |
| Year |
2022 |
| Published |
|
| DOI |
10.1109/ETFA52439.2022.9921427 |
| Abstract |
Manufacturing companies are facing two major trends affecting their business operations: "automatization" and "collaboration". Companies have realized that they still need humans on the shop floor beside the availability of high levels of automation solutions in the market. This realization has created a new Industrial Revolution known as "Industry 5.0". While the primary concern in Industry 4.0 is about achieving high levels of full automation, Industry 5.0 focuses on creating synergies between humans and autonomous machines in semi-automated manufacturing systems toward flexible, resilient, and sustainable systems. The critical element of human-automation synergies is a better understanding of the excellent cooperation between humans and making a better collaboration between humans and autonomous machines inspired by it. The proposed Intelligent Collaborative Manufacturing Space (ICMS) aims to create a framework for supporting collaborations based on smart sensor networks and data science techniques. Four main elements or sub-spaces characterize this "Intelligent Workspace": (i) the Working Space, (ii) the Monitoring Space, (iii) the Modelling Space, and (iv) the Decision Space. The ICMS is a framework envisioned for supporting the effective collaboration between humans and automated and semi-automated production assets based on activity recognition and prediction paired with machine learning optimization algorithms. Amethodologyfor developing ICMSs is described in detail in this paper. |
| Author Keywords |
Operator 4.0; Industry 5.0; Intelligent Space; Collaboration; Human-Machine; Human-Human |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000934103900008 |
| WoS Category |
Automation & Control Systems; Engineering, Industrial; Engineering, Manufacturing |
| Research Area |
Automation & Control Systems; Engineering |
| PDF |
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