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Holistic System-Analytics as an Alternative to Isolated Sensor Technology: A Condition Monitoring Use Case

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Title:Holistic System-Analytics as an Alternative to Isolated Sensor Technology: A Condition Monitoring Use Case
Authors:Martin, Dominik
Kühl, Niklas
Keywords:Analytics and AI for Industry - Specific Applications
Decision Analytics, Mobile Services, and Service Science
condition monitoring, holistic system-analytics, machine learning, sensor, system-wide analytics
Date Issued:08 Jan 2019
Abstract:Sensor technology has become increasingly important (e.g., Industry 4.0, IoT). Large numbers of machines and products are equipped with sensors to constantly monitor their condition. Usually, the condition of an entire system is inferred through sensors in parts of the system by means of a multiplicity of methods and techniques. This so-called condition monitoring can thus reduce the downtime costs of a machine through improved maintenance scheduling. However, for small components as well as relatively inexpensive or immutable parts of a machine, sometimes it is not possible or uneconomical to embed sensors. We propose a system-oriented concept of how to monitor individual components of a complex technical system without including additional sensor technology. By using already existing sensors from the environment combined with machine learning techniques, we are able to infer the condition of a system component, without actually observing it. In consequence condition monitoring or additional services based on the component's behavior can be developed without overcoming the challenges of sensor implementation.
Pages/Duration:8 pages
URI:http://hdl.handle.net/10125/59540
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.124
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Analytics and AI for Industry - Specific Applications


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