Abstract
Given the latest trends toward the implementation of Industry 4.0 principles, the proposed research work combines human assistance technologies such as Virtual and Augmented Reality with advanced data analysis techniques and tools to develop a comprehensive strategy for Predictive Maintenance planning and execution. On one hand, using Augmented and Virtual Reality technologies, workers are effectively assisted during maintenance operations towards better performances and lower error rates. On the other hand, Predictive Maintenance entails strategies for maintenance planning based on machines’ current conditions to avoid unnecessary overhauls.
Thus a seamless integration of Virtual and Augmented Reality with Predictive Maintenance is envisaged to bring substantial advantages in terms of productivity and competitiveness enhancement for manufacturing systems and represents a step ahead toward the real implementation of the Industry 4.0 vision.
Original language | English |
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Title of host publication | 29th European Modeling and Simulation Symposium, EMSS 2017, Held at the International Multidisciplinary Modeling and Simulation Multiconference, I3M 2017 |
Editors | Francesco Longo, Michael Affenzeller, Miquel Angel Piera, Agostino G. Bruzzone, Emilio Jimenez |
Pages | 546-551 |
Number of pages | 6 |
ISBN (Electronic) | 9781510847651 |
Publication status | Published - 2017 |
Event | The 29th European Modeling & Simulation Symposium EMSS 2017 - Barcelona, Spain Duration: 18 Sept 2017 → 20 Sept 2017 http://www.msc-les.org/conf/emss2017/ |
Publication series
Name | 29th European Modeling and Simulation Symposium, EMSS 2017, Held at the International Multidisciplinary Modeling and Simulation Multiconference, I3M 2017 |
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Conference
Conference | The 29th European Modeling & Simulation Symposium EMSS 2017 |
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Country/Territory | Spain |
City | Barcelona |
Period | 18.09.2017 → 20.09.2017 |
Internet address |
Keywords
- Industry 4.0
- Virtual / Augmented Reality
- Data Stream Analysis
- Predictive Maintenance
- Symbolic Regression