Knowledge-based support of system analysis for the analysis of Failure modes and effects

Wirth, Rüdiger; Berthold, Bernd; Krämer, Anita; Gerhard, Péter

doi:10.1016/0952-1976(96)00014-0

Cited by 70 publications

(38 citation statements)

References 3 publications

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“…The procedure is still considered by most organizations as laborious and costly both in terms of money and time. The lack of methodological guidelines to conduct an FMEA and the employment of natural language in recording the FMEA-related information have been identified as two fundamental weaknesses in the conventional FMEA [3]. Due to these weaknesses many FMEA efforts have had poor results due to the inconsistent natural language descriptions of the functions, the components, or the systems and the failures they undergo.…”

Section: Linguistic Terminologymentioning

confidence: 99%

Failure Prevention in Design Through Effective Catalogue Utilization of Historical Failure Events

Lough

Stone

Tumer

2008

J Fail. Anal. and Preven.

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The science of failure prevention relies heavily on the experience of personnel on a project. As the nation is about to face a tremendous decline in the experienced workforce due to the baby boomer generation's retirement, it is critical to begin focusing on capturing their knowledge. Cataloging and communicating the knowledge of potential failures is critical to prevent engineering disasters. Many companies have adopted failure-reporting systems that allow them to record their engineering failures to promote failure prevention. While recording this information is vital to learning from past mistakes, often the information is not stored so that engineers and designers can easily recall this valuable linguistic information and use it to improve designs. Therefore, more effective systems for cataloging and utilizing corporate memory of recorded failure events are needed. This article presents the design of a computational linguistic database to support the failure prevention tool, the risk in early design (RED) method. RED promotes failure prevention by identifying failure risks as early as the conceptual phase of product design, where impacts of failure prevention are greatest. It uses a database populated by historical failure event information to present specific areas that are at risk of failure in a product.

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Section: Linguistic Terminologymentioning

confidence: 99%

Failure Prevention in Design Through Effective Catalogue Utilization of Historical Failure Events

Lough

Stone

Tumer

2008

J Fail. Anal. and Preven.

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“…However, without a proper way to archive and manage the knowledge generated through it, the task of performing an FMEA becomes quite laborious. The WIFA (short form for ''knowledge-based FMEA'' in German) project (Wirth et al 1996) is aimed at providing a solution to the knowledge management problem for FMEA. It facilitates past knowledge reuse by populating and managing knowledge bases to support descriptions of various products and processes.…”

Section: Motivation and Outline Of Proposed Workmentioning

confidence: 99%

Cognitive map-based system modeling for identifying interaction failure modes

et al. 2011

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Past few decades have seen an upsurge in failure analysis techniques capable of dealing with reliability issues up front in the early stages of the product development process. Most of these approaches are centered on component-specific failures. However, with the advent of highly complex systems that derive functionalities from multiple physical phenomena domains, more emphasis is required on identifying failures arising due to various system interactions, which is largely absent in existing failure analysis approaches. Owing to the causal nature of system interaction failures, the use of cognitive maps in system modeling and simulation for failure analysis is highly suitable. This paper proposes a structured framework for the development and use of cognitive mapbased system models capable of capturing all types of failure modes, including interaction failures. The applicability of the proposed framework is demonstrated with the example of an electric water heater.

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“…The FIS modelling approach presented in this paper allows both the HE and IM aspects to be represented in the same model as compared with most of the approaches reported in the literature that focus on IM and functional failure [8].…”

Section: Definition 1: Fault (Iec50)mentioning

confidence: 99%

A model-based approach for systematic risk analysis

Flaus

2008

Proceedings of the Institution of Mechanical Engineers, Part O:

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A modelling approach based on a mixed structural/functional graph that allows the simultaneous representation of the structural and the functional aspects of a system is presented. This model provides a framework to formalize risk analysis while being as simple as possible. The focus of the proposed approach is to achieve in a common analysis a functional failure analysis and the identification of physical damage, these being the two complementary parts of a full risk analysis. The resulting failure propagation graph is useful for model-based reasoning for fault diagnosis, the detection of dangerous situations, and the prediction of critical events. In addition, the approach is modular and reusable. The approach is illustrated by its use on an example.

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Knowledge-based support of system analysis for the analysis of Failure modes and effects

Cited by 70 publications

References 3 publications

Failure Prevention in Design Through Effective Catalogue Utilization of Historical Failure Events

Failure Prevention in Design Through Effective Catalogue Utilization of Historical Failure Events

Cognitive map-based system modeling for identifying interaction failure modes

A model-based approach for systematic risk analysis

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