Condition monitoring: A new perspective

We present a novel approach to support preventive replacement decisions based on condition monitoring. It is assumed that the condition of a technical unit is measured continuously, with the measurement indicating in which of k ⩾ 2 states the unit is. A new unit is in state S1, and failure occurs the moment a unit leaves state Sk. A unit will only go from state Sj to state Sj+1, and these immediately observed transitions occur at random times. At such transition moments a decision is required on preventive replacement of the unit, which would require preparation time. Such a decision needs to be based on inferences about the total residual time till failure. We present a method for such inferences that relies on minimal model assumptions added to data on state transitions. We illustrate the approach via simulated examples, and discuss possible use of the method and related aspects.