8 resultados para Optimal Maintenance Strategy

em University of Queensland eSpace - Australia


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For leased equipment the lessor incurs penalty costs for failures occurring over the lease period and for not rectifying such failures within a specified time limit. Through preventive maintenance actions the penalty costs can be reduced but this is achieved at the expense of increased maintenance costs. The paper looks at a periodic preventive maintenance policy which achieves a tradeoff between the penalty and maintenance costs. (c) 2005 Elsevier Ltd. All rights reserved.

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Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.

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Recent studies have demonstrated male mate choice for female ornaments in species without sex-role reversal. Despite these empirical findings, little is known about the adaptive dynamics of female signalling, in particular the evolution of male mating preferences. The evolution of traits that signal mate quality is more complex in females than in males because females usually provide the bulk of resources for the developing offspring. Here, we investigate the evolution of male mating preferences using a mathematical model which: (i) specifically accounts for the fact that females must trade-off resources invested in ornaments with reproduction; and (ii) allows male mating preferences to evolve a non-directional shape. The optimal adaptive strategy for males is to develop stabilizing mating preferences for female display traits to avoid females that either invests too many or too few resources in ornamentation. However, the evolutionary stability of this prediction is dependent upon the level of error made by females when allocating resources to either signal or fecundity.

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Effective detection of population trend is crucial for managing threatened species. Little theory exists, however, to assist managers in choosing the most cost-effective monitoring techniques for diagnosing trend. We present a framework for determining the optimal monitoring strategy by simulating a manager collecting data on a declining species, the Chestnut-rumped Hylacola (Hylacola pyrrhopygia parkeri), to determine whether the species should be listed under the IUCN (World Conservation Union) Red List. We compared the efficiencies of two strategies for detecting trend, abundance, and presence-absence surveys, underfinancial constraints. One might expect the abundance surveys to be superior under all circumstances because more information is collected at each site. Nevertheless, the presence-absence data can be collected at more sites because the surveyor is not obliged to spend a fixed amount of time at each site. The optimal strategy for monitoring was very dependent on the budget available. Under some circumstances, presence-absence surveys outperformed abundance surveys for diagnosing the IUCN Red List categories cost-effectively. Abundance surveys were best if the species was expected to be recorded more than 16 times/year; otherwise, presence-absence surveys were best. The relationship between the strategies we investigated is likely to be relevant for many comparisons of presence-absence or abundance data. Managers of any cryptic or low-density species who hope to maximize their success of estimating trend should find an application for our results.

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For leased equipment, the lessor carries out the maintenance of the equipment. Usually, the contract of lease specifies the penalty for equipment failures and for repairs not being carried out within specified time limits. This implies that optimal preventive maintenance policies must take these penalty costs into account and properly traded against the cost of preventive maintenance actions. The costs associated with failures are high as unplanned corrective maintenance actions are costly and the resulting penalties due to lease contract terms being violated. The paper develops a model to determine the optimal parameters of a preventive maintenance policy that takes into account all these costs to minimize the total expected cost to the lessor for new item lease. The parameters of the policy are (i) the number of preventive maintenance actions to be carried out over the lease period, (ii) the time instants for such actions, and (iii) the level of action. (c) 2005 Elsevier B.V. All rights reserved.

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The advent of molecular markers as a tool to aid selection has provided plant breeders with the opportunity to rapidly deliver superior genetic solutions to problems in agricultural production systems. However, a major constraint to the implementation of marker-assisted selection (MAS) in pragmatic breeding programs in the past has been the perceived high relative cost of MAS compared to conventional phenotypic selection. In this paper, computer simulation was used to design a genetically effective and economically efficient marker-assisted breeding strategy aimed at a specific outcome. Under investigation was a strategy involving the integration of both restricted backcrossing and doubled haploid (DH) technology. The point at which molecular markers are applied in a selection strategy can be critical to the effectiveness and cost efficiency of that strategy. The application of molecular markers was considered at three phases in the strategy: allele enrichment in the BC1F1 population, gene selection at the haploid stage and the selection for recurrent parent background of DHs prior to field testing. Overall, incorporating MAS at all three stages was the most effective, in terms of delivering a high frequency of desired outcomes and at combining the selected favourable rust resistance, end use quality and grain yield alleles. However, when costs were included in the model the combination of MAS at the BC1F1 and haploid stage was identified as the optimal strategy. A detailed economic analysis showed that incorporation of marker selection at these two stages not only increased genetic gain over the phenotypic alternative but actually reduced the over all cost by 40%.

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For repairable items, the manufacturer has the option to either repair or replace a failed item that is returned under warranty. In this paper, we look at a new warranty servicing strategy for items sold with two-dimensional warranty where the failed item is replaced by a new one when it fails for the first time in a specified region of the warranty and all other failures are repaired minimally. The region is characterised by two parameters and we derive the optimal values for these to minimise the total expected warranty servicing cost. We compare the results with other repair-replace strategies reported in the literature. (C) 2003 Elsevier Ltd. All rights reserved.

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Abstract: Purpose – The aim of this research is to determine the optimal upgrade and preventive maintenance actions that minimize the total expected cost (maintenance costs+penalty costs). Design/methodology/approach – The problem is a four-parameter optimization with two parameters being k-dimensional. The optimal solution is obtained by using a four-stage approach where at each stage a one-parameter optimization is solved. Findings – Upgrading action is an extra option before the lease of used equipment, in addition to preventive maintenance action. Upgrading action makes equipment younger and preventive maintenance action lowers the ROCOF. Practical implications – There is a growing trend towards leasing equipment rather than owning it. The lease contract contains penalties if the equipment fails often and repairs are done within reasonable time period. This implies that the lessor needs to look at optimal preventive maintenance strategies in the case of new equipment lease, and upgrade actions plus preventive maintenance in the case of used equipment lease. The paper deals with this topic and is of great significant to business involved with leasing equipment. Originality/value – Nowadays many organizations are interested in leasing equipment and outsourcing maintenance. The model in this paper addresses the preventive maintenance problem for leased equipment. It provides an approach to dealing with this problem.