English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Maintenance optimization of naval ship equipment is crucial in terms ofnational defense. However, the mixed effect of the maintenance and the puredeterioration processes in the observed data hinders an exact comparisonbetween candidate maintenance policies. That is, the observed data-annualfailure counts of naval ships reflect counteracting actions between themaintenance and deterioration. The inference of the latent deterioratingprocess is needed in advance for choosing an optimal maintenance policy to becarried out. This study proposes a new framework for the separation of the truedeterioration effect by predicting it from the current maintenance effectthrough the multi-state Markov model. Using an annual engine failure count of99 ships in the Korean navy, we construct the framework consisting ofimputation, transition matrix design, optimization, and validation. Thehierarchical Gaussian process model is used for the imputation and thethree-state Markov model is applied for the estimation of parameters in thedeterioration and maintenance effect. To consider the natural (deterioration)and artificial (maintenance) effect respectively, the Bayesian HMM model with acategorical distribution is employed. Computational experiments under multiplesettings showed the robustness of the estimated parameters, as well as anaccurate recovery of the observed data, thereby confirming the credibility ofour model. The framework could further be employed to establish a reliablemaintenance system and to reduce an overall maintenance cost.

A Multi-state Markov Model to Infer the Latent Deterioration Process From the Maintenance Effect on Reliability Engineering of Ships