Stochastic models are developed for the reliability analysis of repairable systems, based upon the non-homogenous Poisson process, as recommended by Ascher and Feingold (1984). In particular, the proportional intensities model (PIM) introduced by Cox (1972), is extended and modified for this purpose. The suitability of the PIM is demonstrated on three groups of hypothetical data sets from the f...

Heavy equipment overhaul facilities such as aircraft service centers and rail-yards face the challenge of minimizing the makespan for a set of preventive maintenance (PM) tasks, requiring singleor multiple-skills, within workforce availability constraints. In this paper, we examine the utility of evolution strategies (ES) to this problem. Comparison of the computational efforts of ES with exhau...

For modern semiconductor manufacturing, a large number of interrelated equipment data are automatically collected. These data are usually used for fault detection and classification (FDC). However, unusual measurements may reflect a wafer defect or a change in equipment conditions. Early detection of the equipment condition changes assists with efficient maintenance. This study aimed to develop...

We consider a manufacturing system with preventive maintenance that produces a single part type. An inventory is maintained according to a machine age dependent hedging point policy. We conjecture that, for such a system, the failure frequencies can be reduced through preventive maintenance resulting in possible increase in system performance. Traditional preventive maintenance policies, such a...

The purpose of this research is to estimate the repair effects a repairable system undergoes repeated failures and repairs. Data was collected on a cement kiln incurring150 failures and 5 shutdowns for overhaul. Causes of failure were identified as operational, mechanical or electrical. The unit was restarted but with an (expected) improved failure rate by virtue of the repair. Repair improveme...

BACKGROUND Prospective memory (PM) denotes the ability to remember to perform actions in the future. It has been argued that standard laboratory paradigms fail to capture core aspects of PM. METHODOLOGY/PRINCIPAL FINDINGS We combined functional MRI, virtual reality, eye-tracking and verbal reports to explore the dynamic allocation of neurocognitive processes during a naturalistic PM task wher...

This work presents an improved genetic algorithm (IGA) for minimizing periodic preventive maintenance costs in series-parallel systems. The intrinsic properties of a repairable system, including the structure of reliability block diagrams and component maintenance priorities are considered by the proposed IGA. The proposed component importance measure considers these properties, identifies key ...

We introduce the preventive maintenance scheduling problem with interval costs (PMSPIC), which is to schedule preventive maintenance (PM) of the components of a system over a finite and discretized time horizon, given a common set-up cost and component costs dependent on the lengths of the maintenance intervals. We present a 0-1 integer linear programming (0-1 ILP) model for the PMSPIC; the mod...

The paper generalizes a preventive maintenance optimization problem to multi-state systems, which have a range of performance levels. Multi-state system reliability is defined as the ability to satisfy given demand. The reliability of system elements is characterized by their hazard functions. The possible preventive maintenance actions are characterized by their ability to affect the effective...

In a manufacturing system, lot sizing and maintenance are interdependent interact with each other. Few studies jointly investigated production management considering system degradation. However, during the process, critical component performance will undergo inevitable degradation over time. For example, equipment wears out due to both its own internal causes external environment. To monitor in...