A general solution of the preventive maintenance problem when data are right-censored

In this paper, we suggest a new approach to solve the preventive maintenanc e problem, when available data are right-censored. The new approach is base d on fitting a member of a new family of distributions, recently introduced , where the distribution fitting procedures use partial moments of first or first and second degree only. The effectiveness of the new approach under various distribution assumptions is demonstrated. It is shown that the part ial distribution data, available in the form of censored observations, does not detract meaningfully from the optimality of the derived solution.