Optimal Grouping of Heterogeneous Components in Series and Parallel Systems Under Archimedean Copula Dependence

This paper considers series and parallel systems comprising n components drawn from a heterogeneous population consisting of m different subpopulations. The components within each subpopulation are assumed to be dependent, while the subpopulations are independent of each other. The authors also assume that the subpopulations have different Archimedean copulas for their dependence. Under this setup, the authors discuss the series and parallel systems reliability for three different cases, respectively. The authors use the theory of stochastic orders and majorization to establish the main results, and finally present some numerical examples to illustrate all the results established here.