Dynamic reliability and sensitivity analysis based on HMM models with Markovian signal process Gámiz Pérez, María Luz Navas-Gómez, Fernando Raya Miranda, Rocío Segovia García, María del Carmen Double chain Hidden Markov Model EM-algorithm Maintenance Sensitivity measures Sensors The authors are grateful to three anonymous reviewers and the Editor for many valuable comments and suggestions, which have helped to improve the quality of the article. This work is jointly supported by the Spanish Ministry of Science and Innovation-State Research Agency through grants numbered PID2020-120217RB-I00 and PID2021-123737NB-I00, and by the Spanish Junta de Andalucia through grant number B-FQM-284-UGR20 and the IMAG Maria de Maeztu, Spain grant CEX2020-001105-/AEI/10.13039/501100011033. All authors read and approved the final manuscript. The main objective of this paper is to build stochastic models to describe the evolution-in-time of a system and to estimate its characteristics when direct observations of the system state are not available. One important application area arises with the deployment of sensor networks that have become ubiquitous nowadays with the purpose of observing and controlling industrial equipment. The model is based on hidden Markov processes where the observation at a given time depends not only on the current hidden state but also on the previous observations. Some reliability measures are defined in this context and a sensitivity analysis is presented in order to control for false positive (negative) signals that would lead to believe erroneously that the system is in failure (working) when actually it is not. System maintenance aspects based on the model are considered, and the concept of signal-runs is introduced. A simulation study is carried out to evaluate the finite sample performance of the method and a real application related to a water-pump system monitored by a set of sensors is also discussed. 2023-09-15T07:46:56Z 2023-09-15T07:46:56Z 2023-11 info:eu-repo/semantics/article M.L. Gámiz et al. Dynamic reliability and sensitivity analysis based on HMM models with Markovian signal process. Reliability Engineering and System Safety 239 (2023) 109498. [https://doi.org/10.1016/j.ress.2023.109498] https://hdl.handle.net/10481/84437 10.1016/j.ress.2023.109498 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elsevier