Abstract
This paper proposes a multi-agent-based collaborative virtual manufacturing environment (VME) to save energy consumption and improve efficiency in the manufacturing process. In order to achieve the high autonomy of the manufacturing system, a multi-agent system (MAS) is designed to build a collaborative VME. In this new VME environment, edge computing is embedded to strengthen the cyber resource utilization and system economy. Moreover, an efficient communication channel between networks is proposed. The subsequent cooperation and collaboration protocols among agents are designed to ensure flexible and process-oriented operations. Furthermore, the fuzzy resolution algorithm is employed to resolve the competition conflicts among function-similar MASs in the distributed manufacturing scenario. Lastly, a simulation and case study are performed to evaluate the performance of the proposed VME in Internet of Things (IoT)-based manufacturing. The analysis results have demonstrated the feasibility and effectiveness of the proposed VME system.
Highlights
The virtual manufacturing environment (VME) is an environment that executes manufacturing processes [1]
Bearing the above observations in mind, this article intends to carry on the comprehensive development of a collaborative VME through the integration of multi-agent system (MAS) and edge computing techniques with a case study
Data processing performed by edge computing enables the application of a cluster of mechanisms to implement the analysis of acquired signal and instant decision making on-site [26]
Summary
School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China School of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong NSW 2522, Australia
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.