The optimal age replacement strategy under epistemic uncertainty

Applying the theory of uncertainty is a good approach to study the reliability of a system when there is a little frequency of suitable data. Based on this theory, the policy of age replacement is considered assuming the system lifetime follows Weibull distribution. The unknown parameters are estimated according to evidence theory that affects the epistemic uncertainty. The Dempster-Shafer as well as Yager rules are applied to aggregate the judgements and mental estimates of two or more experts. After determining the unknown parameters, the optimal replacement time is derived using the long-run cost criterion. The results show that the Dempster-Shafer rule is more accurate than yager rule, but Yager’s rule is more conservative than Dempster-Shafer’s rule.