The section examines results and interpretation from interviews conducted with experts mentioned in Table 4.1. However, in the course of interview process, the researcher presented a list of pre-stated and additional interview questions in the line of remaining useful life prediction.
i. How would you describe the degradation data? ii. How do you manage the data?
iii. What are the component degradation mechanisms? iv. How are the data extracted?
v. What is the process of extracting data?
vi. How would you describe taxonomy and ontology in this context? vii. How would you describe the degradation mechanism?
viii. What are the prominent degradation mechanisms?
ix. What are the components which are prone to these degradation mechanisms?
x. What are the key features of nozzle guide vanes component and described it?
xi. What is the essence of development test event?
xii. How would you describe the degradation model for prediction?
xiii. Is there a link between component level and assembly level data in a multi-component system?
xiv. How would you demonstrate component rejection, replacement and reuse?
The interview questions were validated with my supervisors, members of my research team and colleagues from research centres. The researcher discussed the interview questions with supervisors, who in turn assessed the questions before approval to ensure it is in line with the research and follows the required standards, ethics and processes. The researcher conducted a one-to-one interview with centre colleagues to ascertain the validity of the questions as a test case for further interviews with experts in sponsoring organisation. The
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responses to the face-to-face and semi-structured interview questions posed to the experts are presented. A total of 11 semi-structured interviews questions were used to conduct the interviews with different experts listed in Table 4-1.
Based on question 1, Participant A described degradation data as large set of structure and unstructured data. Participant B and D emphasised that degradation data are complex containing numeric and textual data. Participant C referred to degradation as deterioration, which includes tear, crack and wear. Regarding question 2, Respondent A opined that degradation or maintenance data are stored in databases. Respondent B highlighted that degradation data are managed using Maximo and FRACAS databases. Respondent C noted that data are stored in different locations depending on the nature of the maintenance information. Respondent D provided a clear response by indicating the in-service data used for resolving customers’ issues are available in the Maximo database, while FRACAS database contains specification and design work information. Respondent E highlighted that data are stored in different locations or sources e.g. hardcopy documents archives and softcopy in Excel. Furthermore, the data stored in these databases are components, features, and deterioration for capturing the understanding of the physical system.
Relating to question 3, Participants A to G noted some of the component degradation mechanisms including corrosion, deformation, wear and fracture. A request was made to view the database for more mechanisms.
With question 4, Respondents F and G responded to this question. While Respondent F emphasised that data in databases are extracted using an in- house application, Respondent G reiterated that extraction tool is a “recognition tool” designed by an in-house expert using Java. Respondent G also noted that the database contains different modules called containing concepts / terms of deterioration (taxonomy). Database contains information such as the names of products, customers, service types, system types, components, features and mechanisms. This study focuses on products, components / parts / commodities, features and mechanisms.
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In question 5, Respondent F explains the process of importing data into excel and using the tool to select the concepts add-on to identify and extract relevant terms. Respondent G opined that the data extraction include (i) concepts/terms only and (ii) relationship extraction between a component and mechanisms. While concepts are currently being extracted using add-ons to recognise and retrieve terms, relationship extraction based on subject-verb-object (SVO) add- on is applied to retrieve components and mechanisms (Jiang, 2012). Example “a blade has crack” (“blades” as component and “crack as mechanisms”).
For question 6, Participants F and G responded to this question. Participant F described a taxonomy as synonyms of degradation mechanisms and ontology as a collection of different taxonomy for specific space e.g. ontology module can be a deterioration process containing synonyms of degradation mechanisms. Respondent F emphasised that study should focus on corrosion, deformation, fracture and wear as the major degradation mechanisms affecting gas turbine mechanical components in the hot section. Respondent G highlighted that ‘split’ can be another name of ‘tear’ or ‘cut’, but the underlying meaning might be different from the nature of the mechanisms. Respondent G noted that ontology in this context relates to the different excel sheets, which are used to store the taxonomies for each ontology module.
Regarding question 7, Respondent D relates degradation mechanisms to loosing performance depending on usage. Respondent E noted degradation mechanism results from use of an asset and when the limit or end of life is approached, the rate of performance tends to reduce. Respondent F described degradation mechanisms as a process which makes an item to lose its strength. Respondent G highlighted that degradation mechanism affects the functionality of assets. In question 8, Respondent A noted that nozzle guide vane and turbine blade are prone to degradation mechanisms in the hot section. Respondents F and G made mentioned of the nozzle guide vane, blades and seal segment.
For question 9, Participant A gave a vivid description of the nozzle guide vane as the central focus of this study. Participant A stressed that components are mainly
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in compressor, combustor and turbine segments of an engine. However, a jet engine is a multi-component system. For example, nozzle guide vane (NGV) can be either single or in pairs. The NGVs can be between 16 and 20 pairs depending on the manufactured engine. Additionally, a gas turbine is a pressure energy system for velocity and the function of NGV is tuning high pressure gas out of the combustion at 16000C, which undergoes a uniform burning. Participant A gave
key features of the NGV, which include leading edge, trailing edge, gill holes, shroud, cooling holes, TBC and fir tree root. Participants F and G requested reference to the specific experts such as participant A. Other participants made reference to the engine manuals to get the acceptance limit for engine usage, technical variance of the engine, and events recording management system. With question 10, Respondents A and F provide responses to this question. In the engine testing process or programme, various events occur during testing. Both participants noted that development test event is the test in progress with the sole task of validating the system based on the specified operating conditions. Participant F provided further insights illustrating that degradation model such as the Weibull function is suitable for degradation, reliability and maintenance issues and it is widely used in industry especially aerospace. Participant F described the operation of an engine in a start and stop mode depicting the numbers of component rejection, replacement and reuse. This question provides information to the case study relating to prognostics.
Relating to question 11, Participant F showed that there is link between component level and assembly level. In this context, an individual component is unable to power a system, while collection of components as an assembly has capability to fire a system. Though, at the component level no insight on data, while assembly level has insight on data such as how many were scrapped, how many were reused and replaced and how many repaired components were replaced.
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4.3.1 Comparative analysis of participants’ views
A comparison based on participants’ views is presented and emphases on the current practice relating to component degradation and remaining useful life prediction. The similarities, differences and unique features relating to the experts about the component degradation and failure mechanisms considered are highlighted.
Similarities
i. Use in-house application for data analysis
ii. No set standards for analysis of complex data to predict component failure existed
iii. No standard methodology for estimating component degradation for future replace existed
Difference
i. Terminologies of different terms and concepts are present in the database ii. Definition for failure modes and failure mechanisms vary
Distinct
i. Each participant happens to have distinct level of experience in reliability, which results to difference in interpretation of understanding failure analysis.
ii. The advantages of lessons learned are applicable to different individuals by providing enhancement to existing practice