RT Journal Article
T1 A new analytical method to optimise the preventive maintenance interval by using a semi-Markov process and z-transform with an application to marine diesel engines
A1 Sánchez Herguedas, Antonio
A1 Mena Nieto, Ángel Isidro
A1 Rodrigo Muñoz, Francisco
AB This article presents a novel method based on a semi-Markov process approach and the z transform to calculate the optimal time interval until the preventive maintenance intervention. For this, a mathematical expression that has its origin in the evolution of the maintenance cost of a patrol boat's propulsion engine is developed, represented mathematically by a system of difference equations. This method can be applied to all assets that are subject to wear, which are very common on industrial facilities. This mathematical expression for the preventive interval is a powerful tool for maintenance managers because this saves him from resorting to complicated mathematical methods. In addition to the proposed mathematical formula, the manager needs to know the assets’ failure history data and the costs of maintenance interventions. These data are usually available, making their practical application fast and easy to develop. Due to the method being analytical, it could also serve as an excellent decision support tool. It can be applied to the desired time horizon guaranteeing the obtention of the optimal interval. In many other cases, applying the model can simplify the process of obtaining the asset maintenance programme, from an economic perspective.
PB Elsevier
SN 0951-8320
YR 2021
FD 2021
LK http://hdl.handle.net/10272/19118
UL http://hdl.handle.net/10272/19118
LA eng
NO Sánchez-Herguedas, A., Mena-Nieto, A., Rodrigo-Muñoz, F. : "A new analytical method to optimise the preventive maintenance interval by using a semi-Markov process and z-transform with an application to marine diesel engines". Reliability Engineering and System Safety. Vol. 207, 2021. doi: https://doi.org/10.1016/j.ress.2020.107394
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026