In this paper, we present an inventory pooling model for spare units of critical systems that serve multi-companies. Companies located in the same geographical area can benefit from a coalition to share the storage cost of such spare units, which may be stored as one unit at only one company’s...

Demand for spare parts is typically intermittent and forecasting the relevant requirements constitutes a very challenging exercise. Why is the demand for spare parts intermittent and how can we use models developed in maintenance research to forecast such demand? We attempt to answer these...

This paper presents a two-stage regression model for quantifying different stages of a disease progression with delayed diagnosis time and for identifying the risk factors associated with each stage. Conventional chronic disease progression studies reported replied on the assumption that the...

A model is presented in this paper for maintenance service contract design, negotiation and optimization. The model was developed under the assumption that there are one customer and one unique service provider who is the Original Equipment Manufacturer (OEM) and is called the agent in this...

Remaining useful life (RUL) estimation is regarded as one of the most central components in prognostics and health management (PHM). Accurate RUL estimation can enable failure prevention in a more controllable manner in that effective maintenance can be executed in appropriate time to correct...

This paper presents a case study of condition based maintenance modelling based on measured metal concentrations observed in oil samples of a fleet of marine diesel engines. The decision model for optimising the replacement time of the diesel engines conditional on observed measurements is...

Spare parts demands are usually generated by the need of maintenance either preventively or at failures. These demands are difficult to predict based on historical data of past spare parts usages, and therefore, the optimal inventory control policy may be also difficult to obtain. However, it is...

When complex systems are monitored, multi-observations from several sensors or sources may be available. These observations can be fused through Bayesian theory to give a posterior probabilistic estimate of the underlying state which is often not directly observable. This forms the basis of a...