2020
Oliver Antons; Julia C. Arlinghaus
Designing decision-making authorities for smart factories Proceedings Article
In: pp. 316–322, Elsevier, 2020.
Abstract | Links | BibTeX | Tags: Autonomy, Autonomy & Decision-making Authority, Cyber-physical system, Decision-making, Discrete-event simulation, Distributed control, Industry 4.0, Intelligent Product, Multi-agent system, Smart factory
@inproceedings{antons2020designing,
title = {Designing decision-making authorities for smart factories},
author = {Oliver Antons and Julia C. Arlinghaus},
url = {https://www.sciencedirect.com/science/article/pii/S2212827120306120},
doi = {10.1016/j.procir.2020.04.047},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Procedia CIRP},
volume = {93},
pages = {316--322},
publisher = {Elsevier},
abstract = {Smart factories are an appealing vision, addressing ever increasing challenges in industry. Driven by advances in microcontroller, sensor and networking technologies, all entities, such as machines, products, load carriers, within a smart factory could become intelligent and able to assess their own situation and to attain their own goals successfully. However, local decision may exacerbate achieving global logistics performance due to the entities intrinsic selfishness. In this paper, we explore the trade-off between local decision-making and global performance management and derive first guidelines for the situation-specific design of a distributed control authority for smart factories.},
keywords = {Autonomy, Autonomy \& Decision-making Authority, Cyber-physical system, Decision-making, Discrete-event simulation, Distributed control, Industry 4.0, Intelligent Product, Multi-agent system, Smart factory},
pubstate = {published},
tppubtype = {inproceedings}
}
Smart factories are an appealing vision, addressing ever increasing challenges in industry. Driven by advances in microcontroller, sensor and networking technologies, all entities, such as machines, products, load carriers, within a smart factory could become intelligent and able to assess their own situation and to attain their own goals successfully. However, local decision may exacerbate achieving global logistics performance due to the entities intrinsic selfishness. In this paper, we explore the trade-off between local decision-making and global performance management and derive first guidelines for the situation-specific design of a distributed control authority for smart factories.