Development of an ontology for aerospace engine components degradation in service

This 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

Service Knowledge Capture and Reuse

The 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

A framework development to predict remaining useful life of a gas turbine mechanical component

Power-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

Use of COTS functional analysis software as an IVHM design tool for detection and isolation of UAV fuel system faults

This paper presents a new approach to the development of health management solutions which can be applied to both new and legacy platforms during the conceptual design phase. The approach involves the qualitative functional modelling of a system in order to perform an Integrated Vehicle Health Management (IVHM) design – the placement of sensors and the diagnostic rules to be used in interrogating their output. The qualitative functional analysis was chosen as a route for early assessment of failures in complex systems. Functional models of system components are required for capturing the available system knowledge used during various stages of system and IVHM design. MADe™ (Maintenance Aware Design environment), a COTS software tool developed by PHM Technology, was used for the health management design. A model has been built incorporating the failure diagrams of five failure modes for five different components of a UAV fuel system. Thus an inherent health management solution for the system and the optimised sensor set solution have been defined. The automatically generated sensor set solution also contains a diagnostic rule set, which was validated on the fuel rig for different operation modes taking into account the predicted fault detection/isolation and ambiguity group coefficients. It was concluded that when using functional modelling, the IVHM design and the actual system design cannot be done in isolation. The functional approach requires permanent input from the system designer and reliability engineers in order to construct a functional model that will qualitatively represent the real system. In other words, the physical insight should not be isolated from the failure phenomena and the diagnostic analysis tools should be able to adequately capture the experience bases. This approach has been verified on a laboratory bench top test rig which can simulate a range of possible fuel system faults. The rig is fully instrumented in order to allow benchmarking of various sensing solution for fault detection/isolation that were identified using functional analysis

Towards design of prognostics and health management solutions for maritime assets

With increase in competition between OEMs of maritime assets and operators alike, the need to maximize the productivity of an equipment and increase operational efficiency and reliability is increasingly stringent and challenging. Also, with the adoption of availability contracts, maritime OEMs are becoming directly interested in understanding the health of their assets in order to maximize profits and to minimize the risk of a system's failure. The key to address these challenges and needs is performance optimization. For this to be possible it is important to understand that system failure can induce downtime which will increase the total cost of ownership, therefore it is important by all means to minimize unscheduled maintenance. If the state of health or condition of a system, subsystem or component is known, condition-based maintenance can be carried out and system design optimization can be achieved thereby reducing total cost of ownership. With the increasing competition with regards to the maritime industry, it is important that the state of health of a component/sub-system/system/asset is known before a vessel embarks on a mission. Any breakdown or malfunction in any part of any system or subsystem on board vessel during the operation offshore will lead to large economic losses and sometimes cause accidents. For example, damages to the fuel oil system of vessel's main engine can result in huge downtime as a result of the vessel not being in operation. This paper presents a prognostic and health management (PHM) development process applied on a fuel oil system powering diesel engines typically used in various cruise and fishing vessels, dredgers, pipe laying vessels and large oil tankers. This process will hopefully enable future PHM solutions for maritime assets to be designed in a more formal and systematic way

Predictive Maintenance Modelling for Through-Life Engineering Services

Predictive 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

Data mining and knowledge reuse for the initial systems design and manufacturing: Aero-engine service risk drivers

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

Maintenance Informatics Dashboard Design for Through-life Engineering Services

This 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

The adoption and use of Through-life Engineering Services within UK Manufacturing Organisations

Manufacturing organisations seek ever more innovative approaches in order to maintain and improve their competitive position within the global market. One such initiative that is gaining significance is ‘through-life engineering services’. These seek to adopt ‘whole life’ service support through the greater understanding of component and system performance driven by knowledge gained from maintenance, repair and overhaul activities. This research presents the findings of exploratory research based on a survey of UK manufacturers who provide through-life engineering services. The survey findings illustrate significant issues to be addressed within the field before the concept becomes widely accepted. These include a more proactive approach to maintenance activities based on real-time responses; standardisation of data content, structure, collection, storage and retrieval protocols in support of maintenance; the development of clear definitions, ontologies and a taxonomy of through-life engineering services in support of the service delivery system; lack of understanding of component and system performance due to the presence of ‘No Fault Found’ events that skew maintenance metrics and the increased use of radio-frequency identification technology in support of maintenance data acquisition