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ADAPT an Automatic Diagnosis of Activity and Processes in auTomation environments.pdf (1.732Mb)
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Title
ADAPT: an Automatic Diagnosis of Activity and Processes in auTomation environments
Author
Azkarate Fernandez, IgorMondragon Unibertsitatea
Aguirre Ortuzar, AitorMondragon Unibertsitatea
Uranga Andrés, JosuMondragon Unibertsitatea
Eciolaza, LukaMondragon Unibertsitatea
Research Group
Robótica y automatización
Published Date
2020
Publisher
IEEE
Keywords
Artificial Intelligence algorithms
context awareness
digital twin
emulation ... [+]
Artificial Intelligence algorithms
context awareness
digital twin
emulation
Fault diagnosis
manufacturing automation
Activity recognition [-]
Abstract
In an automated industrial environment, a large volume of data and signals is available, both from sensors and actuators in machinery and from the interaction with operators and users. Operation diagn ... [+]
In an automated industrial environment, a large volume of data and signals is available, both from sensors and actuators in machinery and from the interaction with operators and users. Operation diagnosis can have multiple applications from a learning point of view (e.g. staff training) or in terms of process assessment. This work proposes a methodology for implementing an Intelligent System by means of any interactive system connected through OPC UA standard. A digital twin of the process supports configuration and validation, prior to commissioning. Activity is interpreted and diagnosed according to the context in which it occurs. Step order in sequence, step duration and sequence duration are analyzed in a use case based on a PLC-controlled robotic cell in which it is operated both in automatic and manual mode for adjusting a linear table’s positioning. [-]
URI
https://hdl.handle.net/20.500.11984/5307
Publisher’s version
https://doi.org/10.1109/ETFA46521.2020.9211996
ISBN
978-1-7281-8956-7
ISSN
1946-0759
Published at
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)  Viena. 8-11 de Septiembre. Pp. 945-951, 2020
Document type
Conference paper
Version
Postprint – Accepted Manuscript
Rights
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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  • Conferences - Engineering [234]

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