D
Dragan Banjevic
Researcher at University of Toronto
Publications - 73
Citations - 6874
Dragan Banjevic is an academic researcher from University of Toronto. The author has contributed to research in topics: Condition-based maintenance & Condition monitoring. The author has an hindex of 29, co-authored 73 publications receiving 6172 citations.
Papers
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Journal ArticleDOI
Multi-threaded simulated annealing for a bi-objective maintenance scheduling problem
TL;DR: The obtained results imply the high efficiency and robustness of the proposed heuristic for both solution quality and computational effort.
Book ChapterDOI
Multi-objective Simulated Annealing for a Maintenance Workforce Scheduling Problem: A case Study
Nima Safaei,Dragan Banjevic +1 more
TL;DR: A multi-objective simulated annealing (MOSA) algorithm is described in this chapter to solve a real maintenance workforce scheduling problem (MWSP) aimed at simultaneously minimizing the workforce cost and maximizing the equipment availability.
Journal Article
A recursive method for functionals of Poisson processes
TL;DR: In this paper, a simple recursive method for characterizing Poisson process functionals that requires only the use of conditional probability is described, which is useful for convex hulls, extremes, stable measures, infinitely divisible random variables and Bayesian nonparametric priors.
Proceedings ArticleDOI
Incorporating expert knowledge when estimating parameters of the proportional hazards model
TL;DR: In this paper, the authors present a methodology that can use both experts' knowledge and statistical data to estimate the parameters of PHM, which results in a set of inequalities which in turn define a feasible space for the values of the parameters.
Proceedings ArticleDOI
A Predictive Tool for Remaining Useful Life Estimation of Rotating Machinery Components
TL;DR: In this paper, a model for multiple degradation features of an individual component is introduced and a proportional hazards model is presented, which considers hard failures and multiple degradation feature simultaneously, to predict the mean remaining useful life of a component based on on-line degradation information.