538 research outputs found
Optimal Overhaul-Replacement Policies for Repairable Machine Sold with Warranty
This research deals with an overhaul-replacement policy for a repairable machine sold with Free Replacement Warranty (FRW). The machine will be used for a finite horizon, T (T <ï‚¥), and evaluated at a fixed interval, s (s< T). At each evaluation point, the buyer considers three alternative decisions i.e. Keep the machine, Overhaul it, or Replace it with a new identical one. An overhaul can reduce the machine age virtually, but not to a point that the machine is as good as new. If the machine fails during the warranty period, it is rectified at no cost to the buyer. Any failure occurring before and after the expiry of the warranty is restored by minimal repair. An overhaul-replacement policy is formulated for such machines by using dynamic programming approach to obtain the buyer's optimal policy. The results show that a significant rejuvenation effect due to overhaul may extend the length of machine life cycle and delay the replacement decision. In contrast, the warranty stimulates early machine replacement and by then increases the replacement frequencies for a certain range of replacement cost. This demonstrates that to minimize the total ownership cost over T the buyer needs to consider the minimal repair cost reduction due to rejuvenation effect of overhaul as well as the warranty benefit due to replacement. Numerical examples are presented for both illustrating the optimal policy and describing the behavior of the optimal solution
Spare parts planning and control for maintenance operations
This paper presents a framework for planning and control of the spare parts supply chain inorganizations that use and maintain high-value capital assets. Decisions in the framework aredecomposed hierarchically and interfaces are described. We provide relevant literature to aiddecision making and identify open research topics. The framework can be used to increasethe e¿ciency, consistency and sustainability of decisions on how to plan and control a spareparts supply chain. This point is illustrated by applying it in a case-study. Applicability of theframework in di¿erent environments is also investigated
Modeling Spare Parts Demands Forecast under Two-Dimensional Preventive Maintenance Policy
In maintenance practice, there is such a situation where the spare parts replacement should be carried out at the scheduling time of calendar or usage for whichever comes first. The issue of two-dimensional preventive maintenance usually was not addressed by traditional methods, and at present, few studies were focused on this very topic. Based on these considerations, this paper presented the two-dimensional preventive policy where replacements of spare parts are based on both calendar time and usage time. A novel model was developed to forecast spare parts demands under two-dimensional preventive maintenance policy, and a discrete algorithm was presented for solving the mathematical model. A case study was given to demonstrate its applicability and validity, and it was showed that the presented model can be used to forecast spare parts demands as well as to optimize spare parts and preventive maintenance jointly
Prognostics-Based Two-Operator Competition for Maintenance and Service Part Logistics
Prognostics and timely maintenance of components are critical to the continuing operation of a system. By implementing prognostics, it is possible for the operator to maintain the system in the right place at the right time. However, the complexity in the real world makes near-zero downtime difficult to achieve partly because of a possible shortage of required service parts. This is realistic and quite important in maintenance practice. To coordinate with a prognostics-based maintenance schedule, the operator must decide when to order service parts and how to compete with other operators who also need the same parts. This research addresses a joint decision-making approach that assists two operators in making proactive maintenance decisions and strategically competing for a service part that both operators rely on for their individual operations. To this end, a maintenance policy involving competition in service part procurement is developed based on the Stackelberg game-theoretic model. Variations of the policy are formulated for three different scenarios and solved via either backward induction or genetic algorithm methods. Unlike the first two scenarios, the possibility for either of the operators being the leader in such competitions is considered in the third scenario. A numerical study on wind turbine operation is provided to demonstrate the use of the joint decision-making approach in maintenance and service part logistics
Post-Sale Cost Modeling and Optimization Linking Warranty and Preventive Maintenance
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Imperfect Preventive Maintenance Policies With Unpunctual Execution.
Traditional maintenance planning problems usually presume that preventive maintenance (PM) policies will be executed exactly as planned. In reality, however, maintainers often deviate from the intended PM policy, resulting in unpunctual PM executions that may reduce maintenance effectiveness. This article studies two imperfect PM policies with unpunctual executions for infinite and finite planning horizons, respectively. Under the former policy, imperfect PM actions are periodically performed and the system is preventively replaced at the last PM instant. The objective is to determine the optimal number of PM actions and associated PM interval so as to minimize the long-run average cost rate. While the latter policy specifies that a system is subject to periodic PM activities within a finite planning horizon and there is no PM activity at the end of the horizon. The aim is then to identify the optimal number of PM activities to minimize the expected total maintenance cost. We discuss the modeling and optimization of the two unpunctual PM policies, and then explore the impact of unpunctual executions on the optimal PM decisions and corresponding maintenance expenses in an analytical or numerical way. The resulting insights are helpful for practitioners to adjust their PM plans when unpunctual executions are anticipated
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