A Cyber Physical Interface for Automation Systems—Methodology and Examples

Cyber physical systems (CPS) in a manufacturing and automation context can be referred to different manufacturing process, including design, simulation, control, and verification. However, for data analytics, the concept of CPS is relatively new, and a standard methodology is lacking on how to incor...

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Bibliographic Details
Main Authors: Hung-An Kao, Wenjing Jin, David Siegel, Jay Lee
Format: Article
Language:English
Published: MDPI AG 2015-05-01
Series:Machines
Subjects:
Online Access:http://www.mdpi.com/2075-1702/3/2/93
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spelling doaj-e70f2625073b4fd29fe8f4a38383dd7c2020-11-25T00:03:33ZengMDPI AGMachines2075-17022015-05-01329310610.3390/machines3020093machines3020093A Cyber Physical Interface for Automation Systems—Methodology and ExamplesHung-An KaoWenjing JinDavid SiegelJay LeeCyber physical systems (CPS) in a manufacturing and automation context can be referred to different manufacturing process, including design, simulation, control, and verification. However, for data analytics, the concept of CPS is relatively new, and a standard methodology is lacking on how to incorporate this type of interface for automation applications. This study discusses a modeling methodology for a cyber physical interface and presents the five levels of information for a cyber physical system, that range from the data connection level to the system configuration level. In order to achieve this awareness and health state of the machine and system, a technical approach that uses adaptive health monitoring algorithms is presented. Lastly, an experimental study on a machine tool ball screw is highlighted, in which a predictive model and a cyber physical interface is developed for this application. The outcomes from this study demonstrate that machine health state awareness is feasible, and the core technologies can aim mechanical systems systematically develop its CPS. This can lead to additional product revenue for the manufacturers, and also a potential competitive edge in the market place.http://www.mdpi.com/2075-1702/3/2/93cyber physical systemadaptive algorithmshealth monitoring, ball screw
collection DOAJ
language English
format Article
sources DOAJ
author Hung-An Kao
Wenjing Jin
David Siegel
Jay Lee
spellingShingle Hung-An Kao
Wenjing Jin
David Siegel
Jay Lee
A Cyber Physical Interface for Automation Systems—Methodology and Examples
Machines
cyber physical system
adaptive algorithms
health monitoring, ball screw
author_facet Hung-An Kao
Wenjing Jin
David Siegel
Jay Lee
author_sort Hung-An Kao
title A Cyber Physical Interface for Automation Systems—Methodology and Examples
title_short A Cyber Physical Interface for Automation Systems—Methodology and Examples
title_full A Cyber Physical Interface for Automation Systems—Methodology and Examples
title_fullStr A Cyber Physical Interface for Automation Systems—Methodology and Examples
title_full_unstemmed A Cyber Physical Interface for Automation Systems—Methodology and Examples
title_sort cyber physical interface for automation systems—methodology and examples
publisher MDPI AG
series Machines
issn 2075-1702
publishDate 2015-05-01
description Cyber physical systems (CPS) in a manufacturing and automation context can be referred to different manufacturing process, including design, simulation, control, and verification. However, for data analytics, the concept of CPS is relatively new, and a standard methodology is lacking on how to incorporate this type of interface for automation applications. This study discusses a modeling methodology for a cyber physical interface and presents the five levels of information for a cyber physical system, that range from the data connection level to the system configuration level. In order to achieve this awareness and health state of the machine and system, a technical approach that uses adaptive health monitoring algorithms is presented. Lastly, an experimental study on a machine tool ball screw is highlighted, in which a predictive model and a cyber physical interface is developed for this application. The outcomes from this study demonstrate that machine health state awareness is feasible, and the core technologies can aim mechanical systems systematically develop its CPS. This can lead to additional product revenue for the manufacturers, and also a potential competitive edge in the market place.
topic cyber physical system
adaptive algorithms
health monitoring, ball screw
url http://www.mdpi.com/2075-1702/3/2/93
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