Robust Optimum Life-Testing Plans under Progressive Type-I Interval Censoring Schemes with Cost Constraint

This paper considers optimal design problems for the Weibull distribution, which can be used to model symmetrical or asymmetrical data, in presence of progressive interval censoring life-testing experiments. Two robust approaches, Bayesian and minimax, are proposed deal with dependence D-optimality c-optimality on unknown parameters. Meanwhile, compound method is applied ensure a compromise between precision estimation parameters quantiles. Furthermore, make become more practical, cost constraints taken into account constructing designs. algorithms provided finding solutions. A simulated example real life given illustrate methods. The sensitivity analysis also studied. These new methods help engineers obtain designs censored