Browsing by Author "Okoh, Caxton"
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Item Open Access Development of an ontology for aerospace engine components degradation in service(ScitePress, 2014-12-31) Okoh, Caxton; Roy, Rajkumar; Mehnen, Jorn; Redding, Louis E.; Harrison, AlanThis paper presents the development of an ontology for component service degradation. In this paper, degradation mechanisms in gas turbine metallic components are used for a case study to explain how a taxonomy within an ontology can be validated. The validation method used in this paper uses an iterative process and sanity checks. Data extracted from on-demand textual information are filtered and grouped into classes of degradation mechanisms. Various concepts are systematically and hierarchically arranged for use in the service maintenance ontology. The allocation of the mechanisms to the AS-IS ontology presents a robust data collection hub. Data integrity is guaranteed when the TO-BE ontology is introduced to analyse processes relative to various failure events. The initial evaluation reveals improvement in the performance of the TO-BE domain ontology based on iterations and updates with recognised mechanisms. The information extracted and collected is required to improve service k nowledge and performance feedback which are important for service engineers. Existing research areas such as natural language processing, knowledge management, and information extraction were also examined.Item Open Access A framework development to predict remaining useful life of a gas turbine mechanical component(2017-09) Okoh, Caxton; Roy, Rajkumar; Mehnen, JornPower-by-the-hour is a performance based offering for delivering outstanding service to operators of civil aviation aircraft. Operators need to guarantee to minimise downtime, reduce service cost and ensure value for money which requires an innovative advanced technology for predictive maintenance. Predictability, availability and reliability of the engine offers better service for operators, and the need to estimate the expected component failure prior to failure occurrence requires a proactive approach to predict the remaining useful life of components within an assembly. This research offers a framework for component remaining useful life prediction using assembly level data. The thesis presents a critical analysis on literature identifying the Weibull method, statistical technique and data-driven methodology relating to remaining useful life prediction, which are used in this research. The AS-IS practice captures relevant information based on the investigation conducted in the aerospace industry. The analysis of maintenance cycles relates to the examination of high-level events for engine availability, whereby more communications with industry showcase a through-life performance timeline visualisation. Overhaul sequence and activities are presented to gain insights of the timeline visualisation. The thesis covers the framework development and application to gas turbine single stage assembly, repair and replacement of components in single stage assembly, and multiple stage assembly. The framework is demonstrated in aerospace engines and power generation engines. The framework developed enables and supports domain experts to quickly respond to, and prepare for maintenance and on-time delivery of spare parts. The results of the framework show the probability of failure based on a pair of error values using the corresponding Scale and Shape parameters. The probability of failure is transformed into the remaining useful life depicting a typical Weibull distribution. The resulting Weibull curves developed with three scenarios of the case shows there are components renewals, therefore, the remaining useful life of the components are established. The framework is validated and verified through a case study with three scenarios and also through expert judgement.Item Open Access Maintenance Informatics Dashboard Design for Through-life Engineering Services(Elsevier, 2017-03-02) Okoh, Caxton; Roy, Rajkumar; Mehen, JornThis article introduces maintenance informatics dashboard design approach for visualising maintenance, repair and overhaul events on a timeline. This paper presents a proposed methodology for aggregate visualisation techniques and a 2D graphical plot method as well as a summary of events on a timeline. In this paper, these events are occurrences which are classified and categorised into levels. The occurrences are accumulated over time as historical information and represented in a visual format over a timeline based on an entity relationship diagram. The information modelling technique with respect to data visualisation is emphasised. The result is a single-page-view of maintenance activities. The maintenance activities of aircraft engines are visualised to ease the accessibility of getting accurate and relevant information for making better maintenance decision. The result can be used to gain insight of the root cause of the events from inception to end of life of the engine.Item Open Access Overview of Remaining Useful Life prediction techniques in Through-life Engineering Services(Elsevier, 2014-06-30) Okoh, Caxton; Roy, Rajkumar; Mehnen, Jorn; Redding, Louis E.Through-life Engineering Services (TES) are essential in the manufacture and servicing of complex engineering products. TES improves support services by providing prognosis of run-to-failure and time-to-failure on-demand data for better decision making. The concept of Remaining Useful Life (RUL) is utilised to predict life-span of components (of a service system) with the purpose of minimising catastrophic failure events in both manufacturing and service sectors. The purpose of this paper is to identify failure mechanisms and emphasise the failure events prediction approaches that can effectively reduce uncertainties. It will demonstrate the classification of techniques used in RUL prediction for optimisation of products’ future use based on current products in-service with regards to predictability, availability and reliability. It presents a mapping of degradation mechanisms against techniques for knowledge acquisition with the objective of presenting to designers and manufacturers ways to improve the life-span of components.Item Open Access Predictive maintenance modelling for through-life engineering services(Elsevier, 2017-03-02) Okoh, Caxton; Roy, Rajkumar; Mehnen, JornPredictive maintenance needs to forecast the numbers of rejections at any overhaul point before any failure occurs in order to accurately and proactively take adequate maintenance action. In healthcare, prediction has been applied to foretell when and how to administer medication to improve the health condition of the patient. The same is true for maintenance where the application of prognostics can help make better decisions. In this paper, an overview of prognostic maintenance strategies is presented. The proposed data-driven prognostics approach employs a statistical technique of (i) the parameter estimation methods of the time-to-failure data to predict the relevant statistical model parameters and (ii) prognostics modelling incorporating the reliability Weibull Cumulative Distribution Function to predict part rejection, replacement, and reuse. The analysis of the modelling uses synthetic data validated by industry domain experts. The outcome of the prediction can further proffer solution to designers, manufacturers and operators of industrial product-service systems. The novelty in this paper is the development of the through-life performance approach. The approach ascertains when the system needs to undergo maintenance, repair and overhaul before failure occurs.Item Open Access Service Knowledge Capture and Reuse(Elsevier, 2014-06-30) Roy, Rajkumar; Mehnen, Jorn; Addepalli, Sri; Redding, Louis E.; Tinsley, Lawrence; Okoh, CaxtonThe keynote will start with the need for service knowledge capture and reuse for industrial product-service systems. A novel approach to capture the service damage knowledge about individual component will be presented with experimental results. The technique uses active thermography and image processing approaches for the assessment. The paper will also give an overview of other non-destructive inspection techniques for service damage assessment. A robotic system will be described to automate the damage image capture. The keynote will then propose ways to reuse the knowledge to predict remaining life of the component and feedback to design and manufacturing.