Towards Prognostics and Health Management of Multi-Component Systems with Stochastic Dependence

Roy Assaf, Phuc Do () and Phil Scarf
Additional contact information
Roy Assaf: Autonomous Systems and Robotics Centre, University of Salford
Phuc Do: University of Lorraine
Phil Scarf: Cardiff University

A chapter in Multicriteria and Optimization Models for Risk, Reliability, and Maintenance Decision Analysis, 2022, pp 305-320 from Springer

Abstract: Abstract Prognostics and health management can be described as an emerging engineering discipline which studies and associates the degradation processes to system lifecycle management. It allows for system health state assessment in real-time, as well as predicting its future health states. In this chapter we present a methodology that leads towards PHM of multi-component systems. We cover how to extract health indicators from multi-component systems and present a methodology which makes use of these indicators within a prognostics approach that allows considering stochastic dependence between components. We apply our methodology to data generated by a gearbox accelerated life testing platform. We show that compared to a reduced model for prognostics, where the stochastic dependence between components is not considered, our methodology predicts more accurately the components’ time of end of life.

Keywords: Prognostics and Health Management; Multi-component system; Remaining-useful-life; Degradation; Stochastic dependence; Particle filters (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-89647-8_14

Ordering information: This item can be ordered from
http://www.springer.com/9783030896478

DOI: 10.1007/978-3-030-89647-8_14

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().