

FOLLOWUS
Center for Intelligent Manufacturing Systems and Robots, School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China
College of Computer Science and Technology, Jilin University, Changchun 130012, China
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm 11428, Sweden
[ "Yong-kui LIU,yongkuiliu@163.com" ]
Xue-song ZHANG, E-mail: xs_zhang@126.com
[ "Lin ZHANG,zhanglin@buaa.edu.cn" ]
[ "Fei TAO,ftao@buaa.edu.cn" ]
[ "Li-hui WANG,lihuiw@kth.se" ]
Received:19 February 2019,
Revised:2019-11-28,
Published:2019-11
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Yong-kui LIU, Xue-song ZHANG, Lin ZHANG, et al. A multi-agent architecture for scheduling in platform-based smart manufacturing systems[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(11): 1465-1492.
Yong-kui LIU, Xue-song ZHANG, Lin ZHANG, et al. A multi-agent architecture for scheduling in platform-based smart manufacturing systems[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(11): 1465-1492. DOI: 10.1631/FITEE.1900094.
在过去几年,一些智能制造概念相继被提出,如云制造、工业4.0以及工业互联网。它们共同目的之一是通过构建汇聚资源的平台,实现跨企业资源协同优化配置。在所有这些概念中,一个完整制造系统包括分布式物理制造系统和一个包含从物理制造系统映射的虚拟制造系统平台。我们称这样的制造系统为平台型智能制造系统。因此,一个平台型智能制造系统可看作一个规模巨大的信息物理系统,其中信息部分是平台而物理部分是相应物理制造系统。对一个平台型智能制造系统而言,一个重要问题是如何实现汇聚资源的优化调度。多智能体技术为该问题的解决提供了一种有效方法。本文提出一个面向平台型智能制造系统调度的多智能体架构,包括平台层次的调度多智能体系统和企业层次的调度多智能体系统。提出平台型智能制造系统调度的流程、特征和需求。基于上述架构,提出一个面向平台型智能制造系统的调度模型。通过案例,验证了所提架构和模型的有效性。
During the past years
a number of smart manufacturing concepts have been proposed
such as cloud manufacturing
Industry 4.0
and Industrial Internet. One of their common aims is to optimize the collaborative resource configuration across enterprises by establishing platforms that aggregate distributed resources. In all of these concepts
a complete manufacturing system consists of distributed physical manufacturing systems and a platform containing the virtual manufacturing systems mapped from the physical ones. We call such manufacturing systems platform-based smart manufacturing systems (PSMSs). A PSMS can therefore be regarded as a huge cyber-physical system with the cyber part being the platform and the physical part being the corresponding physical manufacturing system. A significant issue for a PSMS is how to optimally schedule the aggregated resources. Multi-agent technology provides an effective approach for solving this issue. In this paper we propose a multi-agent architecture for scheduling in PSMSs
which consists of a platform-level scheduling multi-agent system (MAS) and an enterprise-level scheduling MAS. Procedures
characteristics
and requirements of scheduling in PSMSs are presented. A model for scheduling in a PSMS based on the architecture is proposed. A case study is conducted to demonstrate the effectiveness of the proposed architecture and model.
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