Browsing by Author "Rushton, Keith R."

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    A design framework for technology prioritisation in the context of through-life engineering services
    (Elsevier, 2021-06-02) Chi, Jie; Latsou, Christina; Erkoyuncu, John Ahmet; Grenyer, Alex; Rushton, Keith R.; Brocklebank, Simon
    Lack of methods on standardising the prioritisation of technologies within the context of Through-life Engineering Services (TES) has been identified. Inspired by the TES value streams and support activity assets, existing within a common TES framework, a new design framework for technologies prioritisation is proposed. A dynamic toolkit to identify the most suitable technology is also developed, using a Quality Function Deployment method, Analytic Hierarchy Process and ROI analysis. A real case study from the defence sector is employed to validate the developed design framework and toolkit; the results show a well-structured guide that can effectively simplify the decision-making process.
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    Perspectives on trading cost and availability for corrective maintenance at the equipment type level
    (Elsevier, 2017-05-29) Erkoyuncu, John Ahmet; Khan, Samir; Eiroa, Alexandre López; Butler, Nigel; Rushton, Keith R.; Brocklebank, Simon
    Characterising maintenance costs has always been challenging due to a lack of accurate prior cost data and the uncertainties around equipment usage and reliability. Since preventive maintenance does not completely prevent corrective repairs in demanding environments, any unscheduled maintenance can have a large impact on the overall maintenance costs. This introduces the requirement to set up support contracts with minimum baseline solutions that warrant the target demand within certain costs and risks. This article investigates a process that has been developed to estimate performance based support contract costs attributed to corrective maintenance. These can play a dominant role in the through-life support of high values assets. The case context for the paper is the UK Ministry of Defence. The developed approach allows benchmarking support contract solutions, and enabling efficient planning decisions. Emphasis is placed on learning from feedback, testing and validating current methodologies for estimating corrective maintenance costs and availability at the Equipment Type level. These are interacting sub-equipment's that have unique availability requirements and hence have a much larger impact on the capital maintenance expenditure. The presented case studies demonstrate the applicability of the approach towards adequate savings and improved availability estimates.
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    A single layer soil water balance model for estimating deep drainage (potential recharge): An application to cropped land in semi-arid North-east Nigeria.
    (Elsevier, 2007-06-15) Eilers, V. H. M.; Carter, Richard C.; Rushton, Keith R.
    The understanding and quantification of groundwater recharge in semi-arid areas are fundamental to sound management of water resources in such areas. A soil water balance model, if designed to adequately represent the physical processes involved, and if carried out with a short enough (daily) time step, can provide realistic estimates of deep drainage (potential recharge) over long periods. We describe a single store (single layer) mass water balance model applicable to semi-arid areas, which recognises the wetting of the near surface during rainfall, with subsequent availability of water for evaporation and transpiration in the days following rainfall. The model allows for the major hydrological processes taking place at or near the soil-vegetation surface including runoff. Model results are presented for North-east Nigeria, for a continuous period of 36 years during which mean annual rainfall was 431 mm (range 321–650 mm) and mean annual modelled deep drainage was 14 mm (range 0–95 mm, with 23 years having zero potential recharge). The modelling results indicate that annual rainfall totals are not the main predictor of annual recharge. The temporal distribution of daily rainfall and the magnitude of the antecedent (pre-season) soil moisture deficit are the strongest determinants of deep drainage at a particular location, in a particular year. Sensitivity analysis of soil and vegetation parameters suggests that deep drainage is most sensitive to water holding capacity and rooting depth. These are key parameters which determine spatial variability of potential recharge. The model is shown to be plausible by examination of the concepts which underlie it, by comparison with field soil moisture measurements, and by the model's ability to represent qualitative observations of crop yield variations from year to year. Future development of the model could include applications to other climatic conditions and the inclusion of other hydrologic processes.