Wang Z., Wang W., Hu C., Liu X., 2013, An Integrated Decision Model for Critical Component Spare Parts Ordering and Condition-based Replacement with Prognostic Information, Chemical Engineering Transactions, 33, 1063-1068.
With advances in condition monitoring (CM) technologies, the joint decision-making paradigm for spare parts ordering as well as condition-based replacement with prognostic information has become a challenging but appealing issue in the systems health management field. To the best of our knowledge, few papers have focused on the joint decision for critical component spare parts ordering and replacement with prognostic information. In this paper we present an integrated decision model for jointly determining the condition-based replacement and critical component spare parts ordering decisions for a functioning component subject to condition monitoring. To do this, the degradation path of the component is modelled using a Wiener process, and the parameters are updated through the combination of the Bayesian method and the expectation maximization (EM) algorithm using real-time CM data. The probability density function (PDF) and cumulative density function (CDF) of the remaining useful life (RUL) are derived, which are then utilized to update the integrated decisions. The main advantage in our proposed decision-making model is that the prognostic information is fully utilized for joint decisions. An additional advantage lies in the updating mechanism of the RUL which enables the integrated decisions to be updated based on in-situ sensor data. The proposed integrated decision model is validated by a numerical example.
