TY - JOUR
T1 - Industrial Internet of Things-Based Prognostic Health Management
T2 - A Mean-Field Stochastic Game Approach
AU - Koulali, Mohammed Amine
AU - Koulali, Sara
AU - Tembine, Hamidou
AU - Kobbane, Abdellatif
N1 - Publisher Copyright:
© 2013 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018
Y1 - 2018
N2 - Recent advances in industrial Internet of Things (IIoT) have dramatically leveraged prognostic health management for industrial systems. Indeed, the cognitive and communication capabilities of IIoT empower their integration in the industrial systems maintenance workflow to ease the transition toward industry 4.0. In this paper, we study a mean field stochastic game for IIoT-based CBM of industrial facilities formulated to favor grouped maintenance for cost reduction. We provide an analytical analysis of the proposed game to characterize its equilibrium operating point: mean-field equilibrium (MFE). We design a learning algorithm to reach the MFE based on a local adjustment of the maintenance rate and the global health state distribution of the monitored components. Numerical evaluation validates the proposed game and ensures maintaining a high fraction of the components in a healthy state by acting on preventive and corrective replacement rates.
AB - Recent advances in industrial Internet of Things (IIoT) have dramatically leveraged prognostic health management for industrial systems. Indeed, the cognitive and communication capabilities of IIoT empower their integration in the industrial systems maintenance workflow to ease the transition toward industry 4.0. In this paper, we study a mean field stochastic game for IIoT-based CBM of industrial facilities formulated to favor grouped maintenance for cost reduction. We provide an analytical analysis of the proposed game to characterize its equilibrium operating point: mean-field equilibrium (MFE). We design a learning algorithm to reach the MFE based on a local adjustment of the maintenance rate and the global health state distribution of the monitored components. Numerical evaluation validates the proposed game and ensures maintaining a high fraction of the components in a healthy state by acting on preventive and corrective replacement rates.
KW - H-learning
KW - Markov chain
KW - Prognostic health management
KW - industrial Internet of Things
KW - mean-field equilibrium
KW - mean-field stochastic games
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U2 - 10.1109/ACCESS.2018.2871859
DO - 10.1109/ACCESS.2018.2871859
M3 - Article
AN - SCOPUS:85054622744
VL - 6
SP - 54388
EP - 54395
JO - IEEE Access
JF - IEEE Access
SN - 2169-3536
M1 - 8471104
ER -