ENBIS Spring Meeting 2026

Session

Data-Driven & AI for Reliability (II)

28 May 2026, 12:50

Conveners

Data-Driven & AI for Reliability (II)

• Maria del Carmen Segovia Garcia (University of Granada)

12. Variable-Domain Multivariate Functional PCA for PHM and RUL Prediction

Mr CEVAHIR YILDIRIM (UC3M)

28/05/2026, 12:50

Spring Meeting

Functional data analysis methods are increasingly used in Prognostic Health Management (PHM) to model degradation from multi-sensor systems. Multivariate Functional Principal Component Analysis (MFPCA) is effective in this context, but its standard formulation assumes that all units are observed over a common time domain. In practice, operational data often exhibit variable domain lengths due...

13. Hybrid modelling through Latent Differential-Regression Analysis (LDRA) for predicting long-term equipment degradation in the Chemical Process Industry

Tiago Rato (University of Coimbra)

28/05/2026, 13:10

Spring Meeting

Long-term equipment degradation decisively affects production cycles of chemical process industries (CPI), and has a major impact on plant safety, operation and economy. Equipment degradation is caused by underlying phenomena that evolve over time with a rate of change that depends on the operating conditions. To tackle this problem, a Latent Differential Regression Analysis (LDRA) methodology...

15. Unsupervised Anomaly Detection in AIS Data from Fishing Vessels

Fernando Navas-Gomez (University of Granada)

28/05/2026, 13:30

Spring Meeting

The increasing availability of AIS (Automatic Identification System) data in the fishing sector offers new opportunities for monitoring and statistical analysis of maritime activity, but it also poses significant methodological challenges. We present an open problem motivated by the study of fishing vessels operating along the coast of Norway, aiming to promote the development and discussion...