2021
DOI: 10.1007/s10661-021-09175-y
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A review about methods for supporting failure risks analysis in eco-assessment

Abstract: This paper critically reviewed 106 scientific papers proposing methods to enrich eco-assessment with failure determination and risk assessment. The provided research perspective is new and significantly different from the reviews in the literature which are mostly limited to analyse the environmental impacts of uncertainties and off-design functioning rather than the failures. The analysis, based on the contributions of the literature over more than 20 years, was carried out manually and allowed to identify an… Show more

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Cited by 6 publications
(4 citation statements)
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“…Spreafico [32] reviewed 106 scientific papers proposing methods available in literature for over 20 years, identifying failures and assessing their hazards during eco-assessment. From the study emerged, a growing interest in the methods related to the product functioning for supporting failure risk analysis in ecoassessment by the scientific community.…”
Section: Environmental Failure Modes and Effects Analysis (E-fmea)mentioning
confidence: 99%
“…Spreafico [32] reviewed 106 scientific papers proposing methods available in literature for over 20 years, identifying failures and assessing their hazards during eco-assessment. From the study emerged, a growing interest in the methods related to the product functioning for supporting failure risk analysis in ecoassessment by the scientific community.…”
Section: Environmental Failure Modes and Effects Analysis (E-fmea)mentioning
confidence: 99%
“…From the review study conducted by Spreafico [32], there appeared a growing interest in the methods related to the product functioning for supporting failure risks analysis in eco-assessment. The Failure Mode and Effects Analysis (FMEA) is a multi-criteria approach, largely used in manufacturing industries in different phases of the product life, inter alia in the design stage, as an effective and consistent risk assessment method in order to improve production and design [33].…”
Section: Identifying Relevant Design Toolsmentioning
confidence: 99%
“…Hidden-mortality risk among patients deemed "low-risk" following high-risk operations Yongliang Sun 1 , Wenquan Niu 2 , Zhiying Yang 1 assume the relative independence of examined factors that is often not tenable in real scenarios (8). A practical way to overcome this challenge is the adoption of more advanced big data-based machine-learning techniques, which was the approach adopted by Sahara et al (4).…”
Section: Commentarymentioning
confidence: 99%