CASOA: An Architecture for Agent-Based Manufacturing System in the Context of Industry 4.0
Author(s) -
Hao Tang,
Di Li,
Shiyong Wang,
Zhijie Dong
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2758160
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The fourth industrial revolution involves the advanced topics, such as industrial Internet of Things, cyber-physical system and smart manufacturing that address increasing demands for mass customized manufacturing. The agent-based manufacturing is a highly distributed control paradigm that can cope with these challenges well. This paper gives an overview of agent-based architectures for manufacturing systems. Besides, a cloud-assisted self-organized architecture is presented by comprising smart agents and cloud to communicate and negotiate through networks. Ontological representations of knowledge base are constructed to provide the information basis for decision-making of agents, which enables dynamic reconfiguration among agents in a collaborative way to achieve agility and flexibility. Furthermore, the agents' interaction behavior is modeled to structure the agents hierarchically to reduce the complexity, because the interactions among agents in distributed system are difficult to understand and predict. The experimental results show that the presented architecture can be easily deployed to build smart manufacturing system and can improve the adaptiveness and robustness of the manufacturing system when dealing with mixed multi-product tasks.
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