Prognostics assessment using fleet-wide ontology

Large complex systems, such as power plants, ships and aircraft, are composed of multiple systems, subsystems and components. When they are considered as embedded in operating systems such as a fleet, mission readiness and maintenance management issues are raised. PHM (Prognostics and Health Management) plays a key role in controlling the performance level of such systems, at least on the basis of adapted PHM strategies and system developments. Moreover considering a fleet implies to provide managers and engineers a relevant synthesis of information and to keep this information updated in terms of the global health of the fleet as well as the current status of their maintenance efforts. In order to achieve PHM at a fleet level, it is thus necessary to manage relevant knowledge arising from both modeling and monitoring of the fleet. In that way, this paper presents a knowledge structuring scheme based on ontologies for fleet PHM management applied to marine domain, with emphasis on prognostics modeling.

[1]  A. F. Adams,et al.  The Survey , 2021, Dyslexia in Higher Education.

[2]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[3]  I. Alsyouf.  The role of maintenance in improving companies' productivity and profitability , 2002 .

[4]  Krishna R. Pattipati,et al.  Condition-based predictive maintenance of industrial power systems , 2002, SPIE Defense + Commercial Sensing.

[5]  Rajkumar Thirumalainambi,et al.  Training data requirement for a neural network to predict aerodynamic coefficients , 2003, SPIE Defense + Commercial Sensing.

[6]  Gregory Provan.  Prognosis and condition-based monitoring: an open systems architecture , 2003 .

[7]  Piero P. Bonissone,et al.  Predicting the Best Units within a Fleet: Prognostic Capabilities Enabled by Peer Learning, Fuzzy Similarity, and Evolutionary Design Process , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[8]  Antoine Grall,et al.  A maintenance policy for two-unit parallel systems based on imperfect monitoring information , 2006, Reliab. Eng. Syst. Saf..

[9]  Jay Lee,et al.  Similarity based method for manufacturing process performance prediction and diagnosis , 2007, Comput. Ind..

[10]  E Hicham,et al.  Failure Mode and Effects Analysis (FMEA) , 2007 .

[11]  Jianbo Yu,et al.  A similarity-based prognostics approach for Remaining Useful Life estimation of engineered systems , 2008, 2008 International Conference on Prognostics and Health Management.

[12]  Mustapha Ouladsine,et al.  A Generic Prognostic Methodology Using Damage Trajectory Models , 2009, IEEE Transactions on Reliability.

[13]  L. V. Wassenhove,et al.  Sustainable Operations Management , 2005 .

[14]  Nathalie Aussenac-Gilles,et al.  Ontology Based Information Retrieval : an application to automotive diagnosis , 2009 .

[15]  Scott Poll,et al.  A Survey of Health Management User Objectives Related to Diagnostic and Prognostic Metrics , 2009 .

[16]  Benoît Iung,et al.  Generic prognosis model for proactive maintenance decision support: application to pre-industrial e-maintenance test bed , 2010, J. Intell. Manuf..

[17]  Ajit Srividya,et al.  A systemic approach to integrated E-maintenance of large engineering plants , 2010, Int. J. Autom. Comput..

[18]  Michael G. Pecht,et al.  A prognostics and health management roadmap for information and electronics-rich systems , 2010, Microelectron. Reliab..

[19]  Carl S. Byington,et al.  Integrated Software Platform for Fleet Data Analysis, Enhanced Diagnostics, and Safe Transition to Prognostics for Helicopter Component CBM , 2010 .

[20]  Alexandre Voisin,et al.  Fleet historical cases for predictive maintenance , 2011 .

[21]  Felice Romano.  Predictive maintenance of railway subsystems using an Ontology based modelling approach , 2011 .

[22]  Benoît Iung,et al.  Fleet-wide health management architecture , 2011 .

[23]  Benoît Iung,et al.  Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas , 2012, Eng. Appl. Artif. Intell..

[24]  Byeng D. Youn,et al.  A generic probabilistic framework for structural health prognostics and uncertainty management , 2012 .

[25]  Philippe Weber,et al.  Using probabilistic relational models for knowledge representation of production systems: A new approach to assessing maintenance strategies , 2012 .

[26]  Damjan Maletič,et al.  The role of maintenance in improving company's competitiveness and profitability: A case study in a textile company , 2014 .