Paper:	Revealing Predictive Maintenance Strategies from Comprehensive Data Analysis of ASTRI-Horn Historical Monitoring Data
Volume:	541, ADASS XXXIII
Page:	193
Authors:	Federico Incardona; Alessandro Costa; Giuseppe Leto; Kevin Munari; Giovanni Pareschi; Salvatore Scuderi; Gino Tosti; the ASTRI project
DOI:	10.26624/MTNN7542
Abstract:	Modern telescope facilities generate data from various sources, including sensors, weather stations, LiDARs, and FRAMs. Sophisticated software architectures using the Internet of Things (IoT) and big data technologies are required to manage this data. This study explores the potential of sensor data for innovative maintenance techniques, such as predictive maintenance (PdM), to prevent downtime that can affect research. We analyzed historical data from the ASTRI-Horn Cherenkov telescope, spanning seven years, examining data patterns and variable correlations. The findings offer insights for triggering predictive maintenance model development in telescope facilities.

Astronomical Society of the Pacific
Conference Series

© Copyright 1988 - 2025 - Astronomical Society of the Pacific
No part of the material protected by this copyright may be reproduced or used in any form other than for personal use without written permission from the ASP.

Page generated in 0.045 seconds