Maintenance Modeling for a System Equipped on Ship

Kitagawa, Takahiro; Yuge, Tetsushi; Yanagi, Shigeru

doi:10.1587/transfun.e100.a.629

Cited by 5 publications

(1 citation statement)

References 8 publications

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“…The literature on maintenance is vast, including Reliability Engineering [4][5][6][7][8][9][10][11][12], maintenance policies and modelling [13][14][15][16][17][18][19][20], and optimal preventive maintenance intervals [21][22][23][24]. However, fewer papers address the problem of uncertainty in lifetime distribution [25][26][27][28], either by analysing several time-based maintenance policies having uncertainty in the parameters of the lifetime distribution [29] or using right-censored data [30], and adopt the Markovian approach of transition between states (operational, preventive, and corrective maintenance intervention) [31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach

Sánchez-Herguedas

Nieto

Rodrigo-Muñoz

et al. 2022

Sensors

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This paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z transform and a semi-Markovian approach is presented to solve these problems and obtain a much more consistent mathematical solution. This methodology is applied to a real case study of the maintenance of large marine engines of vessels dedicated to coastal surveillance in Spain to illustrate its usefulness. It is shown that the use of right-censored failure data significantly decreases the value of the optimal preventive interval calculated by the model. In addition, that optimal preventive interval increases as we consider older failure data. In sum, applying the proposed methodology, the maintenance manager can modify the preventive maintenance interval, obtaining a noticeable economic improvement. The results obtained are relevant, regardless of the number of data considered, provided that data are available with a duration of at least 75% of the value of the preventive interval.

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