Browsing by Author "Harrison, Andrew"

Now showing 1 - 4 of 4
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    Civil aircraft engine operation life resilient monitoring via usage trajectory mapping on the reliability contour
    (Elsevier, 2022-11-04) Zhou, Hang; Farsi, Maryam; Harrison, Andrew; Parlikad, Ajith Kumar; Brintrup, Alexandra
    The civil aircraft engine business is complex in operation. Being an asset-heavy business operating highly complex engineering systems, the optimized fleet life-cycle management is essential yet challenging. The aviation systems are known for critical operation conditions, high-standard reliability demands, and high cost in both asset value and through-life maintenance services. Civil aircraft engines typically require 3 to 4 highly costly overhauls through service life to maintain performance and the time-on-wing (TOW) requirements of the airline operators. Multiple levels of maintenance activities need accurate and long-term planning for engine fleets coordinating manufacturing, transportation, supply chains and system performance, based on the service life of the engines. The life of assets in the aviation industry is measured uniquely by two scales — the flying hour (FH) and the flying cycle (FC). This paper proposed to evaluate the aviation systems’ service life combining both FH and FC, and the reliability of the systems be dynamically quantified via the records and future plans of the flight profiles. The long-term planning of the most significant shop visit (SV) overhauls is therefore optimized by maximizing the fleet TOW availability, considering the business model of ‘charge customers by the flying time’ in the civil aircraft engine business.
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    Data mining and knowledge reuse for the initial systems design and manufacturing: Aero-engine service risk drivers
    (Elsevier, 2013-09-27) Morar, Nicolau; Rajkumar, Roy; Mehnen, Jorn; Redding, Louis E.; Harrison, Andrew
    Service providers of civil aero engines are typically confronted with a high cost of maintenance, replacement and refurbishment of the service damaged components. In such context, service experience becomes a key issue for determining the service risk drivers for operational disruptions and maintenance burden. This paper presents an industrial case study to produce new knowledge on the relationships between degradation and component design to manufacture. The study applied semantic data mining as a methodology for an efficient and the consistent data capture, representation, and analysis. The paper aims at identifying the service risk drivers based on service experience and event data. The analysis shows that the 3 top mechanisms accounting for 32% of the mechanism references have a strong Pareto effect. The paper concludes with missing information links and future research directions.
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    A digital twin architecture for effective product lifecycle cost estimation
    (Elsevier, 2021-06-02) Farsi, Maryam; Ariansyah, Dedy; Erkoyuncu, John Ahmet; Harrison, Andrew
    Lifecycle cost estimation is crucial for high-value manufacturing sectors, in particular at the early product design stage, to maintain their product affordability and manufacturing profitability within the market. Accordingly, it is important to identify through-life cost reduction opportunities. However, this is a challenging task for designers at the early product lifecycle stage due to the lack of complete historical data and the existence of high-level uncertainties within the product and service cost data. Moreover, the complexity of maintenance, repair, and overhaul interventions during the operation stage reduces the designers’ decision-making confidence level at the earlier stages. This paper aims to address these challenges by proposing a novel Digital Twin (DT) architecture that uses adaptive data structure and ontologies to automatically produce the cost model from data mined information throughout a product lifecycle. The DT architecture supports designers by capturing data in terms of consumed and caused cost and automates the data flow to provide an adaptive cost estimation method across the product lifecycle. The DT enables designers to estimate the lifecycle cost at the early stage and to identify the through-life cost reduction opportunities effectively. Thereby, it is expected that the proposed DT supports OEMs to reduce the total lifecycle cost and improve the efficiency of their product development. A case study of lifecycle cost estimation in the machine tool industry is considered for testing the validity of the DT architecture.
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    A super simple life-cycle cost estimation model with minimum data requirement
    (Elsevier, 2020-10-26) Farsi, Maryam; Erkoyuncu, John Ahmet; Harrison, Andrew
    Life-cycle costing is a practical approach to estimate the total cost of ownership in product-service systems. In high-value manufacturing sectors, due to the complication of overhaul invoices, shop visits, repair and maintenance interventions, identifying service cost reduction opportunities can be complex. Moreover, quantifying the impact of key cost drivers on the total cost is challenging due to the lack of complete historical data and high level of uncertainties within the service cost data. To addressthese challenges, a super simple life-cycle cost model architecture is presented. A set of minimum data requirements is identified for the development of the presented cost model. The model architecture comprises of life-cycle cost breakdown structure and work breakdown structure to specify the cost drivers, unit costs and their frequencies. A bottom-up activity-based cost estimation approach is implemented to calculate the total life-cycle cost of a product. The way that the minimum data requirement is applied to the cost estimation structure is explained. In addition, the minimum data is employed to perform a deterministic sensitivity analysis to compare the relative impact of the model input on the total cost. The Monte-Carlo simulation is performed for estimating the uncertainty propagation on the total life-cycle cost. The presented model architecture simplifies life-cycle cost estimations and service control decisions for maintenance, repair, and overhaul actions. A case study of life-cycle cost estimation in the machine tool industry is considered for testing the validity of the cost model architecture.