Browsing by Author "Brocklebank, Simon"

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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.