On the relevance of clustering strategies for collaborative prognostics. Balbi, M., Cattaneo, L., Nucera, D. D., & Macchi, M. IFAC-PapersOnLine, 54(1):37–42, January, 2021. ![On the relevance of clustering strategies for collaborative prognostics [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The innovative concept of Social Internet of Industrial Things is opening a promising perspective for collaborative prognostics in order to improve maintenance and operational policies. Given this context, the present work studies the exploitation of historical and collaborative information for on-line prognostic assessment. In particular, while aiming at a cost-effective prognostic algorithm, with an efficient use of the available data and a proper prediction accuracy, the work remarks the relevance of an optimized clustering strategy for the selection of the useful information.
@article{balbi_relevance_2021,
series = {17th {IFAC} {Symposium} on {Information} {Control} {Problems} in {Manufacturing} {INCOM} 2021},
title = {On the relevance of clustering strategies for collaborative prognostics},
volume = {54},
issn = {2405-8963},
url = {https://www.sciencedirect.com/science/article/pii/S2405896321007023},
doi = {10.1016/j.ifacol.2021.08.004},
abstract = {The innovative concept of Social Internet of Industrial Things is opening a promising perspective for collaborative prognostics in order to improve maintenance and operational policies. Given this context, the present work studies the exploitation of historical and collaborative information for on-line prognostic assessment. In particular, while aiming at a cost-effective prognostic algorithm, with an efficient use of the available data and a proper prediction accuracy, the work remarks the relevance of an optimized clustering strategy for the selection of the useful information.},
language = {en},
number = {1},
urldate = {2021-11-15},
journal = {IFAC-PapersOnLine},
author = {Balbi, Matteo and Cattaneo, Laura and Nucera, Domenico Daniele and Macchi, Marco},
month = jan,
year = {2021},
keywords = {Collaborative prognostics, RUL prediction, clustering, data-driven prognostics},
pages = {37--42},
}
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