Anticipating aging failure using feedback data and expert judgment

Pérès, François; Bouzaïene, Leïla; Bocquet, Jean-Claude; Billy, F.; Haïk, Philippe

doi:10.1016/j.ress.2005.11.063

Cited by 14 publications

(3 citation statements)

References 3 publications

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“…It is also employed to supplement existing data when these are sparse, questionable or only indirectly applicable. In such cases, data is gathered from experts through specially designed methods of verbal or written communication [58]. An interesting approach focusing on the 'quality of information' elicited from experts is presented in [59].…”

Section: Need Of Expert Judgmentmentioning

confidence: 99%

Remaining useful life, technical health, and life extension

Vaidya

Rausand

2011

Proceedings of the Institution of Mechanical Engineers, Part O:

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Life extension has for a long time been an important and highly discussed issue in nuclear and aviation industries, and has recently attracted considerable attention in the subsea oil and gas industry. Decision-making related to life extension is a multidisciplinary problem, but it primarily depends on the remaining useful life. This paper clarifies the concepts of remaining useful life and technical health, and discusses various influencing factors. An overall model with the capability to handle a heterogeneous combination of requirements, such as degradation modelling, uncertain environmental and operational conditions, uncertain sensor data and expert opinion is suggested for life extension decision-making. It is concluded that a physicsbased modelling approach is appropriate for equipment in the subsea oil and gas industry.

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Section: Need Of Expert Judgmentmentioning

confidence: 99%

Remaining useful life, technical health, and life extension

Vaidya

Rausand

2011

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…The different categories, which are the outputs of the coding process, evolved during the analysis. The reviewed literature (Baya & Leifer, 1996; Davidson & Hunsley, 1994; Marsh, 1997; Motte, Andersson, & Bjärnemo, 2004; Nidamarthi, 1999; Pahl & Beitz, 1996; Peres et al, 2007; Pinna et al, 2005) helped to formulate the initial set of categories. This set evolved into the current set of categories while analyzing the DDRs' sentences.…”

Section: Redesign Case Studiesmentioning

confidence: 99%

Requirements and use of in‐service information in an engineering redesign task: Case studies from the aerospace industry

Jagtap

Johnson

2010

J. Am. Soc. Inf. Sci.

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This paper describes the research stimulated by a fundamental shift that is occurring in the manufacture and marketing of aero engines for commercial and defence purposes, away from the selling of products to the provision of services. This research was undertaken in an aerospace company, which designs and manufactures aero engines and also offers contracts, under which it remains responsible for the maintenance of engines. These contracts allow the company to collect far more data about the in-service performance of their engines than was previously available. This paper aims at identifying what parts of this in-service information are required when components or systems of existing engines need to be redesigned, because they have not performed as expected in service. In addition, this paper aims at understanding how designers use this in-service information in a redesign task. In an attempt to address these aims we analysed five case studies involving redesign of components or systems of an existing engine. The findings show that the in-service information accessed by the designers mainly contains the undesired physical actions (e.g. deterioration mechanisms, deterioration effects, etc.) and the causal chains of these undesired physical actions. We identified a pattern in the designers' actions regarding the use of these causal chains. The designers have generated several solutions that utilize these causal chains seen in the in-service information. The findings provide a sound basis for developing tools and methods to support designers in satisfying their in-service information requirements effectively in a redesign task.

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“…Once the structure is finalized, the experts can be asked to give the estimates of probabilities. In this type of problem solving method, it is necessary that the experts agree on definitions and have good clarity about what is expected from them (Peres et al, 2007). It is sometimes difficult to get an expert knowledge in the form required by a BBN model, i.e.…”

Section: Suitability Of Bbn For Technical Health Modelmentioning

confidence: 99%

Prognosis - subsea oil and gas industry

Vaidya

2010

PHM_CONF

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Life extension has been an important and highly discussed issue in nuclear and aviation industries for a long time and it has recently attracted a considerable attention in subsea oil and gas industry. Decision regarding life extension is primarily based on the remaining useful life. The paper explains the technical health and the other factors that influence the remaining useful life. Degradation mechanisms and the lifetime models are discussed, highlighting the limitations of classical approach and the need for Bayesian approach. A model to predict remaining useful life needs to have a capability of handling heterogeneous combination of requirements like degradation modelling, uncertain sensor data handling, and incorporating expert opinion. The paper explores the suitability of using Bayesian Belief Network as a modelling tool for such prediction in subsea oil and gas industry.

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Anticipating aging failure using feedback data and expert judgment

Cited by 14 publications

References 3 publications

Remaining useful life, technical health, and life extension

Remaining useful life, technical health, and life extension

Requirements and use of in‐service information in an engineering redesign task: Case studies from the aerospace industry

Prognosis - subsea oil and gas industry

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