Title: Signal-based Context Comparative Analysis for Identification of Similar Manufacturing Modules
Authors: Chakraborty, Abhishek 
Haubeck, Christopher
Fay, Alexander 
Lamersdorf, Winfried
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
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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