|Title:||Signal-based Context Comparative Analysis for Identification of Similar Manufacturing Modules||Authors:||Chakraborty, Abhishek
|Language:||eng||Keywords:||Behavior Model;Pattern Matching;Petri Net;Sequence Alignment||Subject (DDC):||620 Ingenieurwissenschaften||Issue Date:||1-Jan-2018||Publisher:||Elsevier||Document Type:||Article||Journal / Series / Working Paper (HSU):||IFAC-PapersOnLine||Volume:||51||Issue:||11||Page Start:||276||Page End:||283||Publisher Place:||Amsterdam||Conference:||16th IFAC Symposium on Information Control Problems in Manufacturing (INCOM), 11.-13.06.2018, Bergamo, Italy||Abstract:||
Industry 4.0 connects different machines and their modules to each other. Integrating already existing non-modular machines and establishing the required modularization in such a scenario requires a lot of time-consuming analysis. But Industry 4.0 also allows previously unconnected machines to establish a comparative analysis between each other by comparing monitored results of new and old machines. This analysis allows finding behavior that overlaps between machines and allows to identify parts that can be encapsulated in new or substituted by already known modules. In this paper, we propose a method to identify those overlapping parts by exploiting learned behavior models during runtime and combining production paths with sequence search algorithms by using context information of observable event signals.
|Organization Units (connected with the publication):||Automatisierungstechnik||ISSN:||24058963||Publisher DOI:||10.1016/j.ifacol.2018.08.294|
|Appears in Collections:||3 - Reported Publications|
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