A human-cyber-physical system approach to lean automation using an industrie 4.0 reference architecture
Pantano M, Regulin D, Lutz B, Lee D (2020)
Publication Type: Conference contribution
Publication year: 2020
Journal
Publisher: Elsevier B.V.
Book Volume: 51
Pages Range: 1082-1090
Conference Proceedings Title: Procedia Manufacturing
Event location: Athens, GRC
DOI: 10.1016/j.promfg.2020.10.152
Abstract
The factory of the future requires flexibility and adaptability to satisfy market demands. However, these properties are difficult to ensure when collaborative manipulators are considered. Thus, approaches for integrating these devices, fostering the adoption of new engineering methodologies for augmenting manipulators are studied. In this work we address how integration of human operators with robotic manipulators might accommodate flexibility requirements using a concept of lean automation. To answer this question, we compare the current research in the field, and we propose a design structure which addresses safety, interfaces and design methods. Our results show safety hardware posing considerable constraints on flexibility. The human interface influences the workload perceived by an operator and, Industrie 4.0 reference architectures do not foresee the human and reconfigurable production cells yet. From a design prospective, this study emphasizes the need to take into consideration human and engineering aspects while planning for the factory of the future.
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Germany (DE)How to cite
APA:
Pantano, M., Regulin, D., Lutz, B., & Lee, D. (2020). A human-cyber-physical system approach to lean automation using an industrie 4.0 reference architecture. In George-Christopher Vosniakos, Marcello Pellicciari, Panorios Benardos, Angelos Markopoulos (Eds.), Procedia Manufacturing (pp. 1082-1090). Athens, GRC: Elsevier B.V..
MLA:
Pantano, Matteo, et al. "A human-cyber-physical system approach to lean automation using an industrie 4.0 reference architecture." Proceedings of the 30th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2021, Athens, GRC Ed. George-Christopher Vosniakos, Marcello Pellicciari, Panorios Benardos, Angelos Markopoulos, Elsevier B.V., 2020. 1082-1090.
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