Decision-support methodology to assess risk in end-of-life management of complex systems
| Autor: | Eric Villeneuve, Laurent Geneste, François Pérès, Cédrick Béler, Eric Reubrez |
|---|---|
| Přispěvatelé: | Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), ESTIA Recherche, Ecole Supérieure des Technologies Industrielles Avancées (ESTIA), Laboratoire Génie de Production (LGP), Ecole Nationale d'Ingénieurs de Tarbes |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Engineering Decision support system Decision-support system Computer Networks and Communications 0211 other engineering and technologies Risk management information systems Context (language use) Risk management tools 02 engineering and technology Directed evidential networks [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] 020901 industrial engineering & automation Autre [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] Belief functions Electrical and Electronic Engineering Risk management Risk assessment 021103 operations research business.industry Management science Evidential reasoning approach Computer Science Applications Deconstruction (building) Risk analysis (engineering) Control and Systems Engineering End-of-life management business Information Systems |
| Zdroj: | IEEE Systems Journal IEEE Systems Journal, IEEE, 2017, 11 (3), pp.1579-1588. ⟨10.1109/JSYST.2016.2522183⟩ |
| ISSN: | 1937-9234 1932-8184 |
| DOI: | 10.1109/JSYST.2016.2522183⟩ |
| Popis: | International audience; End-of-life management of complex systems is increasingly important for industry because of growing environmental concerns and associated regulations. In many areas, lack of hindsight and significant statistical information restricts the efficiency of end-of-life management processes and additional expert knowledge is required. In this context and to promote the reuse of secondhand components, a methodology supported by risk assessment tools is proposed. The proposal consists of an approach to combine expert and statistical knowledge to improve risk assessment. The theory of belief functions provides a common framework to facilitate fusion of multisource knowledge, and a directed evidential network is used to compute a measure of the risk level. An additional indicator is proposed to determine the result quality. Finally, the approach is applied to a scenario in aircraft deconstruction. In order to support the scientific contribution , a software prototype has been developed and used to illustrate the processing of directed evidential networks. Index Terms-Belief functions, decision-support system, directed evidential networks, end-of-life management, risk assessment. |
| Databáze: | OpenAIRE |
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