| Title |
Towards an Architecture for Human-aware Modeling and Execution of Production Processes |
| ID_Doc |
76998 |
| Authors |
Neubauer, M; Krenn, F; Majoe, D |
| Title |
Towards an Architecture for Human-aware Modeling and Execution of Production Processes |
| Year |
2015 |
| Published |
Ifac Papersonline, 48, 3 |
| DOI |
10.1016/j.ifacol.2015.06.097 |
| Abstract |
Today's production companies face a variety of challenges arising from increasingly complex and dynamic environments. The advent of pervasive computing has enabled companies to continuously adapt to these changing manufacturing situations. In factories of the future the worker and his or her well-being is seen as a crucial part of manufacturing; situations. These human factors have to be considered in order to achieve sustainable organizational success. Due to advances in the area of wearable sensors, sensing human properties within a manufacturing setting is technically feasible. Sensing human properties, such as the level of comfort or stress, provides additional information. This allows for continuous adaptation of the manufacturing system behavior based on human needs. In this paper, human-aware modeling and the execution of production processes incorporating human properties are illustrated. This is done by applying; the Subject-Oriented Process Management approach in an application scenario. Furthermore, the architecture and the application of the designed system are described with respect to human stress level and dynamic system adaptation. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. |
| Author Keywords |
Adaptive systems; Sensor systems; Multilevel systems; Process models; Business process engineering |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH) |
| EID |
WOS:000375804100050 |
| WoS Category |
Automation & Control Systems |
| Research Area |
Automation & Control Systems |
| PDF |
https://doi.org/10.1016/j.ifacol.2015.06.097
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