Improving Transferability Between Different Engineering Stages in the Development of Automated Material Flow Modules

Daniel Regulin, Thomas Aicher, Birgit Vogel-Heuser

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

To improve the flexibility and robustness of the engineering of automated production systems (aPS) in the case of extending, reducing, or modifying parts, several approaches propose an encapsulation and clustering of related functions, e.g., from electrical, mechanical, or software engineering, based on a modular architecture. Considering the development of these modules, there are different stages, e.g., module planning or functional engineering, that have to be completed. A reference model that addresses the different stages for the engineering of aPS is proposed by the automation markup language (AML). Due to these different stages and the integration of several engineering disciplines, e.g., mechanical, electrical/electronic, or software engineering, information not limited to one discipline are stored redundantly, increasing the effort to transfer information and the risk of inconsistency. Although data formats for the storage and exchange of plant engineering information exist, e.g., AML, fixed domain specific structures and relations of the information, e.g., for automated material flow systems (aMFSs), are missing. This paper presents the integration of a metamodel into the development of modules for aMFS to improve the transferability and consistency of information between the different engineering stages and the increasing level of detail from coarse-grained plant planning to fine-grained functional engineering.

Original languageEnglish
Article number7499821
Pages (from-to)1422-1432
Number of pages11
JournalIEEE Transactions on Automation Science and Engineering
Volume13
Issue number4
DOIs
StatePublished - Oct 2016

Keywords

  • Computer-aided manufacturing
  • flexible manufacturing systems
  • material flow system
  • model-driven engineering
  • production control

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