Preventive maintenance

About: Preventive maintenance is a research topic. Over the lifetime, 6760 publications have been published within this topic receiving 95158 citations.

Continuous-time predictive-maintenance scheduling for a deteriorating system

Abstract: A predictive-maintenance structure for a gradually deteriorating single-unit system (continuous time/continuous state) is presented in this paper. The proposed decision model enables optimal inspection and replacement decision in order to balance the cost engaged by failure and unavailability on an infinite horizon. Two maintenance decision variables are considered: the preventive replacement threshold and the inspection schedule based on the system state. In order to assess the performance of the proposed maintenance structure, a mathematical model for the maintained system cost is developed using regenerative and semi-regenerative processes theory. Numerical experiments show that the s-expected maintenance cost rate on an infinite horizon can be minimized by a joint optimization of the replacement threshold and the a periodic inspection times. The proposed maintenance structure performs better than classical preventive maintenance policies which can be treated as particular cases. Using the proposed maintenance structure, a well-adapted strategy can automatically be selected for the maintenance decision-maker depending on the characteristics of the wear process and on the different unit costs. Even limit cases can be reached: for example, in the case of expensive inspection and costly preventive replacement, the optimal policy becomes close to a systematic periodic replacement policy. Most of the classical maintenance strategies (periodic inspection/replacement policy, systematic periodic replacement, corrective policy) can be emulated by adopting some specific inspection scheduling rules and replacement thresholds. In a more general way, the proposed maintenance structure shows its adaptability to different possible characteristics of the maintained single-unit system.

Life-cycle cost design of deteriorating structures

Abstract: A lifetime optimization methodology for planning the inspection and repair of structures that deteriorate over time is introduced and illustrated through numerical examples. The optimization is based on minimizing the expected total life-cycle cost while maintaining an allowable lifetime reliability for the structure. This method incorporates: (a) the quality of inspection techniques with different detection capabilities; (b) all repair possibilities based on an event tree; (c) the effects of aging, deterioration, and subsequent repair on structural reliability; and (d) the time value of money. The overall cost to be minimized includes the initial cost and the costs of preventive maintenance, inspection, repair, and failure. The methodology is illustrated using the reinforced concrete T-girders from a highway bridge. An optimum inspection/repair strategy is developed for these girders that are deteriorating due to corrosion in an aggressive environment. The effect of critical parameters such as rate of co...

Optimal maintenance of multi-component systems: a review

Abstract: Over the last few decades the maintenance of systems has become more and more complex. One reason for this is that systems consist of many components which depend on each other. On the one hand, interactions between components complicate the modelling and optimization of maintenance. On the other hand, interactions also offer the opportunity to group maintenance which may save costs. It follows that planning maintenance actions is a big challenge and it is not surprising that many scholars have studied maintenance optimization problems for multi-component systems. In some articles new solution methods for existing problems are proposed, in other articles new maintenance policies for multi-component systems are studied. Moreover, the number of papers with practical applications of optimal maintenance of multi-component systems is still growing.

Method for tracking and reporting usage events to determine when preventive maintenance is due for a medical robotic system

Abstract: A medical robotic system comprises a number of components that may be monitored to determine their preventive maintenance needs by recording usage-related information for the monitored components into associated non-volatile memories. When usage of the component exceeds a specified usage threshold, the system displays a warning message on its display screen to have preventive maintenance performed for the component. If the usage continues without such maintenance and exceeds a higher usage threshold, the system displays an error message on its display screen and the system transitions into an error state during which medical procedures are not allowed to be performed. The usage-related information may also be communicated to a remote computer which gathers and processes usage-related information from a number of medical robotic systems to estimate resource requirements for timely performing preventive maintenance on the medical robotic systems, and anticipated service revenues from such maintenance.

A review of multi-component maintenance models with economic dependence

Abstract: In this paper we review the literature on multi-component maintenance models with economic dependence. The emphasis is on papers that appeared after 1991, but there is an overlap with Section 2 of the most recent review paper by Cho and Parlar (1991). We distinguish between stationary models, where a long-term stable situation is assumed, and dynamic models, which can take information into account that becomes available only on the short term. Within the stationary models we choose a classification scheme that is primarily based on the various options of grouping maintenance activities: grouping either corrective or preventive maintenance, or combining preventive-maintenance actions with corrective actions. As such, this classification links up with the possibilities for grouped maintenance activities that exist in practice.