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System Maintainability Estimation with Multi-Peak Time Distribution based on the Bayesian Melding Method Cover

System Maintainability Estimation with Multi-Peak Time Distribution based on the Bayesian Melding Method

By: ,   and    
Open Access
|Jun 2025

Figures & Tables

Fig. 1.

The flowchart of the proposed method.

Fig. 2.

Illustration of the distribution characteristics of datasets 1, 2 and 3; (a)-(c) Histograms and KDE curves for dataset 1, 2 and 3; (d) Probability plot for dataset 1.

Fig. 3.

The p.d.f plots for the prior distributions: (a), (c) and (e) Informative priors for maintenance operations 1, 2 and 4, respectively; (b), (d) and (f) Non-informative priors for maintenance operations 1, 2 and 4, respectively.

Fig. 4.

Maintainability curves for four estimation methods based on the synthetic data.

Fig. 5.

Illustration for the distribution characteristics of practical data; (a)-(c) Histograms and KDE curves for system level data from PT, the three maintenance operation data from PT, and the data from OT; (d) Probability plot for OT data.

Fig. 6.

Maintainability curves for four estimation methods based on practical data.

Hyperparameter estimates for the natural prior distributions_

Hyperparameter source μ^ \hat \mu λ^ \hat \lambda
System3.22113.061.97
Maintenance operation 133.5518.5049.87
Maintenance operation 274.6214.2175.17
Maintenance operation 444.9016.4545.98

Hyperparameter settings for the non-informative priors_

Number of maintenance operation type μ^ \hat \mu λ^ \hat \lambda
132.320.81.341
272.420.41.250
443.100.20.18

Parameter settings for maintenance operations_

Number of maintenance operation typeMean parameterVariance parameterSample size
133.4915.07132
275.3564.5924
317.888.33187
444.4523.1396
597.05160.3912
625.2910.81172
7129.12942.914
811.218.98154
958.0039.0653
Language: English
Page range: 110 - 121
Submitted on: Nov 6, 2024
Accepted on: Apr 30, 2025
Published on: Jun 17, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2025 Mochao Pei, Jianping Hao, Cuijuan Gao, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.