Browsing by Author "Morar, Nicolau"

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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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    ItemOpen Access
    Modelling the influence of laser drilled recast layer thickness on the fatigue performance of CMSX-4
    (Elsevier, 2018-11-02) Morar, Nicolau; Roy, Rajkumar; Gray, Simon; Nicholls, John R.; Mehnen, Jorn
    This paper introduces a novel approach to fatigue life prediction modelling considering the laser drilling effect on film cooling holes of turbine vanes. The methodology proposed is based on a stress-life model such as the Basquin law and the introduction of manufacturing damage effect. The proposed empirical model gives a unique versatility compared to other stress-life models by considering surface damage such as the recast layer produced by the laser drilling process. The proposed empirical model has been thoroughly tested and validated using existing fatigue data. The statistical analysis shows that the proposed model is adequate for estimating the fatigue life of laser drilled specimens considering the recast layer thicknesses effect. The proposed model also can estimate the life of untested specimens even when only a small sample of fatigue data is available, thereby reducing the required testing data.