Vol. 6 No. 4 (2015): IJPHM Special Issue on Uncertainty in PHM

The International Journal of Prognostics and Health Management (IJPHM) is the premier online open access journal related to multidisciplinary research on Prognostics, Diagnostics, and System Health Management. This special issue focuses on computational methods and practical applications dealing with the representation, interpretation, quantification, and management of uncertainty in prognostics and health management.

Prognostics, the science of prediction, is inherently affected by several sources of uncertainty (natural variability, data uncertainty, and model uncertainty). It is important to rigorously account for these sources of uncertainty while predicting the behavior of engineering systems, and compute the overall uncertainty in the remaining useful life prediction. Uncertainties that exhibit complex, non-linear interactions need to be aggregated using computational methods. If there is a large uncertainty associated with the remaining useful life prediction, then such information may not be useful for meaningful decision-making. Therefore, recent research efforts have focused on developing methods to characterize, interpret, incorporate, and quantify uncertainty in prognostics, quantify the risk associated with system operation decisions, and eventually facilitate risk-informed decision-making activities such as fault mitigation, mission re-planning, etc.

Published: 2015-12-02

Technical Papers

Improved Probabilistic Modeling of Multi-Site Fatigue Cracking

Abdallah Al Tamimi, Mohammad Modarres
Abstract 173 | PDF Downloads 188 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2288

Uncertainty in PHM

Shankar Sankararaman, Sankaran Mahadevan, Marcos E. Orchard
Abstract 278 | PDF Downloads 289 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2289

Probabilistic Prognosis with Dynamic Bayesian Networks

Gregory Bartram, Sankaran Mahadevan
Abstract 294 | PDF Downloads 397 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2290

Uncertainty in Prognostics and Systems Health Management

Shankar Sankararaman, Kai Goebel
Abstract 411 | PDF Downloads 435 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2319

Impact of Prognostic Uncertainty in System Health Monitoring

Robert M. Vandawaker, David R. Jacques, Jason K. Freels
Abstract 509 | PDF Downloads 11005 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2320

Hybrid Particle Petri Nets for Systems Health Monitoring under Uncertainty

Quentin Gaudel, Elodie Chanthery, Pauline Ribot
Abstract 183 | PDF Downloads 170 | DOI https://doi.org/10.36001/ijphm.2015.v6i4.2323