A study on self-reconfiguration of a knowledgeable manufacturing system

Author:

Xue C G1,Yan H S1

Affiliation:

1. Southeast University Research Institute of Automation Jiangsu, People's Republic of China

Abstract

This paper deals with a new approach to the self-reconfiguration of the knowledgeable manufacturing system (KMS), which is based on knowledge meshes and agent meshes. To this end, new concepts of a knowledge mesh (K-M) and an agent mesh (A-M) are proposed as well as a new K-M and A-M based approach to knowledge representation for advanced manufacturing modes. A multiple set on the K-M is also formally defined as well as the mapping relationships between the multiple sets and the K-M. The union, intersection and minus operations on the multiple sets and the algorithms of K-M operations are proposed. In addition, preprocessing rules and the mapping between the multiple sets and the new K-M are explored in detail. On the basis of these, the relational database-based realizations of the K-M and its multiple sets are presented. Functional structure and realization of the self-reconfiguration subsystem of KMS are also presented. Finally, the self-reconfiguration method based on the K-M and A-M is exemplified by the self-reconfiguration of the management information system (MIS) software used in a vehicle body plant at Nanjing in China, which shows the method to be very effective.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Self-reconfiguration and optimisation of knowledge meshes with similar knowledge points;International Journal of Computer Integrated Manufacturing;2016-01-04

2. Parameter analysis and identification of the multiple-advanced manufacturing mode diffusion model;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2014-09-01

3. Clustering and selection of knowledge meshes of knowledgeable manufacturing systems based on decomposition of fuzzy relational data;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2014-07-02

4. An iterative learning method for multi-cycle flexible production/inventory control under random demands;Journal of Intelligent & Fuzzy Systems;2014

5. Self-Representation for Self-Configuration and Monitoring in Agent-Based Flexible Automation Systems;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2013-01

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