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An Attempt for an Industry 4.0 Inspired Cloud-Supported Approach for Predictive Maintenance on the Example of Refill Friction Stir Spot Welding (RFSSW)

Authors: Henry Hameister;

An Attempt for an Industry 4.0 Inspired Cloud-Supported Approach for Predictive Maintenance on the Example of Refill Friction Stir Spot Welding (RFSSW)

Abstract

<div class="section abstract"><div class="htmlview paragraph">This paper presents an approach to how existing production systems can benefit from Industry 4.0 driven concepts. This attempt is based on a communication gateway and a cloud-based system, that hosts all algorithms and models to calculate a prediction of the tool wear. As an example we will show the Refill Friction Stir Spot Welding (RFSSW), a solid state joining technique, which is examined at the Institute of Production Engineering (LaFT) of the Helmut-Schmidt-University, University of the Federal Armed Forces Hamburg, for years.</div><div class="htmlview paragraph">RFSSW is a sub-section of friction welding, where a rotating tool that consists out of three parts is used to heat up material to a dough-like state. Since Refill Friction Stir Spot Welding produces a selective dot-shaped connection of overlapping materials, the production requirements are similar to riveting or resistance spot welding. In contrast to other bonding techniques, Refill Friction Stir Spot Welding can be integrated within the production process without major interferences or changes. At the LaFT we build a prototype from which we collected a big amount of data which we are now trying to analyze with methods that are known from the Industrie 4.0.</div><div class="htmlview paragraph">For the Industry 4.0 idea, the production environment respectively the welding equipment acts like an Internet of things device, that publishes its data to the cloud and retrieves a calculated result.</div></div>

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
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