B
Benoît Iung
Researcher at University of Lorraine
Publications - 158
Citations - 4363
Benoît Iung is an academic researcher from University of Lorraine. The author has contributed to research in topics: Predictive maintenance & Proactive maintenance. The author has an hindex of 30, co-authored 147 publications receiving 3719 citations. Previous affiliations of Benoît Iung include Henri Poincaré University & Centre national de la recherche scientifique.
Papers
More filters
Journal ArticleDOI
Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas
TL;DR: A bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance and an increasing trend of the literature related to these domains is shown.
Journal ArticleDOI
Design and management of manufacturing systems for production quality
Marcello Colledani,Tullio Tolio,Anath Fischer,Benoît Iung,Gisela Lanza,Robert Schmitt,József Váncza,József Váncza +7 more
TL;DR: In this paper, a new paradigm aiming at going beyond traditional six-sigma approaches is proposed, which is extremely relevant in technology intensive and emerging strategic manufacturing sectors, such as aeronautics, automotive, energy, medical technology, micro-manufacturing, electronics and mechatronics.
Journal ArticleDOI
Remaining useful life estimation based on stochastic deterioration models: A comparative study
TL;DR: A stochastic process (Wiener process) combined with a data analysis method (Principal Component Analysis) is proposed to model the deterioration of the components and to estimate the RUL on a case study.
Journal ArticleDOI
A proactive condition-based maintenance strategy with both perfect and imperfect maintenance actions
TL;DR: An adaptive maintenance policy is proposed which can help to select optimally maintenance actions (perfect or imperfect actions), if needed, at each inspection time, according to a remaining useful life (RUL) based-inspection policy.
Journal ArticleDOI
Formalisation of a new prognosis model for supporting proactive maintenance implementation on industrial system
TL;DR: This paper proposes the deployment and experimentation of a prognosis process within an e-maintenance architecture based on the combination of both a probabilistic approach for modelling the degradation mechanism and of an event one for dynamical degradation monitoring.