Model based design of knowledge bases in multi agent systems for enabling automatic reconfiguration capabilities of material flow modules

Daniel Regulin, Daniel Schutz, Thomas Aicher, Birgit Vogel-Heuser

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

Dealing with the requirement to produce many different products at the same automated production system, flexible material flow modules, which are connected to a material flow system (MFS) are required. Therefore a definition of the architecture and interfaces of such modules is provided by a model based engineering approach and an appropriate meta model. Hence, a reduced engineering effort for setting up flexible MFS could be reached. Since the flexible composition of the modules should be performed without (re-)programming, an intelligent agent based control concept will be introduced. Based on the agents' knowledge, the procedure of online system configuration can be performed. Therefore, a main point are geometrical parameters for the online definition of interfaces for communication to neighboring modules. Additionally, the knowledge bases of the agents in the multi agent system can be derived automatically from the model. Furthermore, the communication concept, which has to consider the real-time requirements for synchronization of module interfaces is presented. An exemplary system shows how the reconfiguration triggered by connecting or disconnecting a module can be performed. Subsequently, the performance of the automatic reconfiguration procedure is evaluated regarding reconfiguration time.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
PublisherIEEE Computer Society
Pages133-140
Number of pages8
ISBN (Electronic)9781509024094
DOIs
StatePublished - 14 Nov 2016
Event2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 - Fort Worth, United States
Duration: 21 Aug 201624 Aug 2016

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2016-November
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
Country/TerritoryUnited States
CityFort Worth
Period21/08/1624/08/16

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