Attention-based deep survival model for time series data

Xingyu Li, Vasiliy Krivtsov and Karunesh Arora

Reliability Engineering and System Safety, 2022, vol. 217, issue C

Abstract: In the era of internet of things and Industry 4.0, smart products and manufacturing systems emit signals tracking their operating condition in real-time. Survival analysis shows its strength in modeling such signals to determine the condition of in-service equipment and products to yield critical operational decisions, i.e., maintenance and repair. One appealing aspect of survival analysis is the possibility to include subjects in the model which did not have their failure yet or when the exact failure time is unknown.

Keywords: Survival analysis; Internet of things; Deep learning; Sequence modeling; Prognostics (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:217:y:2022:i:c:s0951832021005408

DOI: 10.1016/j.ress.2021.108033

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