127 resultados para maintenance costs


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Objective: The purpose of this study was to estimate costs and quality of life (QoL) of late-stage glaucoma patients in 4 European countries. Methods: Retrospective review of medical charts of patients with POAG who were followed in a low-vision or vision rehabilitation center in one of 4 countries for at least 1 year was used to determine patient characteristics, health status, and health care resource use. Visual impairment was measured by best-corrected visual acuity (Snellen score). Patients were also interviewed over the telephone in order to assess their health-related QoL (using EuroQol EQ-5D) and use of resources including: the number of visits to rehabilitation centers, visits to hospital and non-hospital specialists, the use of low-vision devices, medication, tests, and the use of hired home help. The costs associated with resource use were calculated from the perspective of a third-party payer of health and social care based on resource usage and unit costs in each country. Results: Patients undergoing visual rehabilitation in France (n=21), Denmark (n=59), Germany (n=60), and the United Kingdom (n=22) were identified, interviewed and had their medical charts reviewed. Annual maintenance costs of late-stage glaucoma amounted to €830 (±445) on average. Average home help costs were more than 3 times higher. QoL, on average, was 0.65 (±0.28). QoL was positively correlated with the level of visual acuity in the patients' best eye. On the other hand, visual acuity was also positively correlated to health care costs, but negatively correlated to costs of home help. Conclusions: The study was limited by its observational, uncontrolled design. The finding that late-stage glaucoma is associated with higher home help costs than health care maintenance costs suggests that potential savings from a better preventive treatment are to be found for social care payers rather than health care payers. © 2008 Informa UK Ltd All rights reserved.

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Abstract. Modern business practices in engineering are increasingly turning to post manufacture service provision in an attempt to generate additional revenue streams and ensure commercial sustainability. Maintainability has always been a consideration during the design process but in the past it has been generally considered to be of tertiary importance behind manufacturability and primary product function in terms of design priorities. The need to draw whole life considerations into concurrent engineering (CE) practice has encouraged companies to address issues such as maintenance, earlier in the design process giving equal importance to all aspects of the product lifecycle. The consideration of design for maintainability (DFM) early in the design process has the potential to significantly reduce maintenance costs, and improve overall running efficiencies as well as safety levels. However a lack of simulation tools still hinders the adaptation of CE to include practical elements of design and therefore further research is required to develop methods by which ‘hands on’ activities such as maintenance can be fully assessed and optimised as concepts develop. Virtual Reality (VR) has the potential to address this issue but the application of these traditionally high cost systems can require complex infrastructure and their use has typically focused on aesthetic aspects of mature designs. This paper examines the application of cost effective VR technology to the rapid assessment of aircraft interior inspection during conceptual design. It focuses on the integration of VR hardware with a typical desktop engineering system and examines the challenges with data transfer, graphics quality and the development of practical user functions within the VR environment. Conclusions drawn to date indicate that the system has the potential to improve maintenance planning through the provision of a usable environment for inspection which is available as soon as preliminary structural models are generated as part of the conceptual design process. Challenges still exist in the efficient transfer of data between the CAD and VR environments as well as the quantification of any benefits that result from the proposed approach. The result of this research will help to improve product maintainability, reduce product development cycle times and lower maintenance costs.

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Universities planning the provision of space for their teaching requirements need to do so in a fashion that reduces capital and maintenance costs whilst still providing a high-quality level of service. Space plans should aim to provide sufficient capacity without incurring excessive costs due to over-capacity. A simple measure used to estimate over-provision is utilisation. Essentially, the utilisation is the fraction of seats that are used in practice, or the ratio of demand to supply. However, studies usually find that utilisation is low, often only 20–40%, and this is suggestive of significant over-capacity.

Our previous work has provided methods to improve such space planning. They identify a critical level of utilisation as the highest level that can be achieved whilst still reliably satisfying the demand for places to allocate teaching events. In this paper, we extend this body of work to incorporate the notions of event-types and space-types. Teaching events have multiple ‘event-types’, such as lecture, tutorial, workshop, etc., and there are generally corresponding space-types. Matching the type of an event to a room of a corresponding space-type is generally desirable. However, realistically, allocation happens in a mixed space-type environment where teaching events of a given type are allocated to rooms of another space-type; e.g., tutorials will borrow lecture theatres or workshop rooms.

We propose a model and methodology to quantify the effects of space-type mixing and establish methods to search for better space-type profiles; where the term “space-type profile” refers to the relative numbers of each type of space. We give evidence that these methods have the potential to improve utilisation levels. Hence, the contribution of this paper is twofold. Firstly, we present informative studies of the effects of space-type mixing on utilisation, and critical utilisations. Secondly, we present straightforward though novel methods to determine better space-type profiles, and give an example in which the resulting profiles are indeed significantly improved.

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Following automation of lighthouses around the coastline of Ireland, reports of accelerated deterioration of interior granite stonework have increased significantly with an associated deterioration in the historic structure and rise in related maintenance costs. Decay of granite stone- work primarily occurs through granular disintegration with the effective grusification of granite surfaces. A decay gradient exists within the towers whereby the condition of granite in the lower levels is much worse than elsewhere. The lower tower levels are also regions with highest rela- tive humidity values and greatest salt concentrations. Data indicate that post-automation decay may have been trig- gered by a change in micro-environmental conditions within the towers associated with increased episodes of condensation on stone surfaces. This in turn appears to have facilitated deposition and accumulation of hygro- scopic salts (e.g. NaCl) giving rise to widespread evidence of deliquescence in the lower tower levels. Evidence indicates that the main factors contributing to accelerated deterioration of interior granite stonework are changes in micro-environmental conditions, salt weathering, chemical weathering through the corrosive effect of strongly alkaline conditions on alumino-silicate minerals within the granite and finally, the mica-rich characteristics of the granite itself which increases its structural and chemical susceptibility to subaerial weathering processes by creating points of weakness within the granite. This case study demonstrates how seemingly minor changes in micro-environmental conditions can unintentionally trigger the rapid and extensive deterioration of a previously stable rock type and threaten the long-term future of nationally iconic opera- tional historic structures.

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Electric vehicles (EV) do not emit tailpipe exhaust fumes in the same manner as internal combustion engine vehicles. Optimal benefits can only be achieved, if EVS are deployed effectively, so that the tailpipe emissions are not substituted by additional emissions in the electricity sector. This paper examines the potential contributions that Plug in Hybrid Electric Vehicles can make in reducing carbon dioxide. The paper presents the results of the generation expansion model for Northern Ireland and the Republic of Ireland built using the dynamic programming based long term generation expansion planning tool called the Wien Automatic System Planning IV tool. The model optimizes power dispatch using hourly electricity demand curves for each year up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. In order to simulate the effect of PHEV, two distinct charging scenarios are applied based on a peak tariff and an off peak tariff. The importance and influence of the charging regime on the amount of energy used and gaseous emissions displaced is determined and discussed.

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An underground work (such as a tunnel or a cavern) has many, well known, environmental qualities such as: no physical barriers crossing the land, less maintenance costs than an analogous surface structure, less expenses for heating and conditioning; a localized emission of noise, gas, dust during operation and, finally, a better protection against seismic actions.
It cannot be forgotten, anyway, that some negative environmental features are present such as, for example, : perturbation, pollution and drainage of the groundwater; settlements; disposal of waste rock.
In the paper the above mentioned concepts are discussed and analysed to give a global overview of all this aspects.

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Objective: To compare caries incidence following two different tooth replacement strategies for partially dentate older patients; namely functionally orientated treatment according to the principles of the Shortened Dental Arch (SDA) and conventional treatment using Removable Partial Dentures (RPDs). Method:A randomised controlled clinical trial (RCT) was conducted of partially dentate patients aged 65 years and older. Patients were randomly allocated to two different treatment groups: the RPD group and the SDA group. Each member of the RPD group was restored to complete arches with cobalt-chromium RPDs used to replace missing teeth. Patients in the SDA group were restored to a shortened arch of 10 occluding pairs of natural and replacement teeth using adhesive bridgework. All of the operative treatment was completed by a single operator. Caries incidence was measured over a 2-year period following treatment intervention and recorded using the International Caries and Detection System (ICDAS). Result:In total, 89 patients completed the RCT (45 SDAs and 44 RPDs). Patients in the RPD group recorded a significantly higher incidence of new carious lesions (p<0.001) and recurrent carious lesions (p<0.001) compared to the SDA group. A mixed model of covariance (ANCOVA) revealed that treatment group (p<0.001) and co-morbidity (p<0.001) were significant predictors of caries incidence. Conclusion:Two years after provision of prosthodontic treatment there was a significantly higher incidence of new and recurrent caries lesions in subjects provided with RPDs compared with SDA treatment. This will have a significant impact on the ongoing maintenance costs for these two treatment groups.

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Under the European Union Renewable Energy Directive each Member State is mandated to ensure that 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020. The Irish Government intends to achieve this target with a number of policies including ensuring that 10% of all vehicles in the transport fleet are powered by electricity by 2020. This paper investigates the impact of the 10% electric vehicle target in Ireland in 2020 using a dynamic programming based long term generation expansion planning model. The model developed optimizes power dispatch using hourly electricity demand curves up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. Two distinct scenarios are analysed based on a peak and off-peak charging regimes in order to simulate the effects of the electric vehicles charging in 2020. The importance and influence of the charging regimes on the amount of energy used and tailgate emissions displaced is then determined.

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Different reproductive strategies of males and females may lead to the evolution of differences in their energetic costs of reproduction, overall energetic requirements and physiological performances. Sexual dimorphism is often associated with costly behaviours (e.g. large males might have a competitive advantage in fighting, which is energetically expensive). However, few studies of mammals have directly compared the energy costs of reproductive activities between sexes. We compared the daily energy expenditure (DEE) and resting metabolic rate (RMR) of males and females of two species of mole-rat, Bathyergus janetta and Georychus capensis (the former is sexually dimorphic in body size and the latter is not) during a period of intense digging when males seek females. We hypothesized that large body size might be indicative of greater digging or fighting capabilities, and hence greater mass-independent DEE values in males of the sexually dimorphic species. In contrast to this prediction, although absolute values of DEE were greater in B. janetta males, mass-independent values were not. No differences were apparent between sexes in G. capensis. By comparison, although RMR values were greater in B. janetta than G. capensis, no differences were apparent between the sexes for either species. The energy cost of dimorphism is most likely to be the cost of maintenance of a large body size, and not the cost of behaviours performed when an individual is large.

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The preventive knowledge of serviceability times is a critical factor for the quantification of after-sales services costs of a vehicle. Predetermined motion time system are frequently used to set labor rates in industry by quantifying the amount of time required to perform specific tasks. The first such system is known as Methods-time measurement (MTM). Several variants of MTM have been developed differing from each other on their level of focus. Among them MTM-UAS is suitable for processes that average around 1-3 min. However experimental tests carried out by the authors in Elasis (Research Center of FIAT Group) demonstrate that MTM-UAS is not the optimal approach to measure serviceability times. The reason is that it doesn't take into account ergonomic factors. In the present paper the authors propose to correct the MTM-UAS method including in the task analysis the study of human postures and efforts. The proposed approach allows to estimate with an "acceptable" error the time needed to perform maintenance tasks since the first phases of product design, by working on Digital Mock-up and human models in virtual environment. As a byproduct of that analysis, it is possible to obtain a list of maintenance times in order to preventively set after-sales service costs. © 2012 Springer-Verlag.

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In semiconductor fabrication processes, effective management of maintenance operations is fundamental to decrease costs associated with failures and downtime. Predictive Maintenance (PdM) approaches, based on statistical methods and historical data, are becoming popular for their predictive capabilities and low (potentially zero) added costs. We present here a PdM module based on Support Vector Machines for prediction of integral type faults, that is, the kind of failures that happen due to machine usage and stress of equipment parts. The proposed module may also be employed as a health factor indicator. The module has been applied to a frequent maintenance problem in semiconductor manufacturing industry, namely the breaking of the filament in the ion-source of ion-implantation tools. The PdM has been tested on a real production dataset. © 2013 IEEE.

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In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

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Process monitoring and Predictive Maintenance (PdM) are gaining increasing attention in most manufacturing environments as a means of reducing maintenance related costs and downtime. This is especially true in industries that are data intensive such as semiconductor manufacturing. In this paper an adaptive PdM based flexible maintenance scheduling decision support system, which pays particular attention to associated opportunity and risk costs, is presented. The proposed system, which employs Machine Learning and regularized regression methods, exploits new information as it becomes available from newly processed components to refine remaining useful life estimates and associated costs and risks. The system has been validated on a real industrial dataset related to an Ion Beam Etching process for semiconductor manufacturing.

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Through the examination of Camões's Os Lusíadas , Sena's Os Grão-Capitães and Saramago's A Jangada de Pedra , this article explores violence as a means of shaping Portuguese identity in different historical contexts, and how these works portray the continued recourse to violence as Portugal moves from colonizing to postcolonial nation.