2015 IEEE 13th International Conference on Industrial Informatics (INDIN) 2015
DOI: 10.1109/indin.2015.7281911
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On applying MDE for generating reconfigurable automation systems

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Cited by 15 publications
(3 citation statements)
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“…In this metamodel, a structural joint of components is named as interface for flows of material, energy and information as well as a geometric joint for assembly. On the other hand, there is another metamodel RC4PA [56] for plant automation focusing on the reconfiguration mechanism of the system. In this metamodel, the control system is divided into several mechatronic components.…”
Section: Analyses On Metamodel Inconsistenciesmentioning
confidence: 99%
“…In this metamodel, a structural joint of components is named as interface for flows of material, energy and information as well as a geometric joint for assembly. On the other hand, there is another metamodel RC4PA [56] for plant automation focusing on the reconfiguration mechanism of the system. In this metamodel, the control system is divided into several mechatronic components.…”
Section: Analyses On Metamodel Inconsistenciesmentioning
confidence: 99%
“…The industry also recognizes that reconfigurable machine tools (RMTs) are essential enablers of RMS; that reconfigurable assembly lines are, at least in theory, easier to achieve than RMS because of the less stringent tolerances; and that hybrid human-machine RMS are advantageous because they make use of the flexibility which is in-built in human nature but at a relatively low cost (ElMaraghy, 2005); Wiendahl et al, 2007. The study of reconfigurability in manufacturing extends to new approaches for control (e.g. Priego et al, 2015 andDurkop et al, 2014) and strategy (e.g. Fasth-Berglund and Stahre, 2013).…”
Section: Introductionmentioning
confidence: 99%
“…[15] introduces the concept of Mechatronic Component (MC) as the code in charge of controlling a part of the process, and it analyzes when it is possible to recover its functionality after a controller fault. In [16], the concept of backup MC for state tracking is proposed. The novel contributions of this work go beyond them as follows:…”
Section: Introductionmentioning
confidence: 99%