The interoperability of exergy and Life Cycle Thinking in assessing manufacturing sustainability: A review of hybrid approaches

作者: Valeria Selicati , Nicola Cardinale , Michele Dassisti

DOI: 10.1016/J.JCLEPRO.2020.124932

关键词: ExergyInteroperabilitySustainabilityOrder (exchange)Process (engineering)Risk analysis (engineering)Life-cycle assessmentAmbiguityVariety (cybernetics)Computer science

摘要: Abstract Today, the Life Cycle Assessment (LCA) is most employed tool for assessing sustainability of products and processes, both from an environmental, social economic point view. Exergy defined by literature as amount useful work that can be derived a real system when it brought into equilibrium with its environment. In literature, considered outstanding concept applied to enhance effectiveness ordinary evaluation models such LCA. The proposes variety hybrid approaches combine Exergetic Analysis (EA) LCA different combination frameworks. aim this paper describe potential each method characterize degree interoperability between EA them provide. Nevertheless, there are drawbacks seem too challenging overcome: inconsistencies in interpretation results due difficulty inventory phase ambiguity choice correct alternative standard databases; link old techniques refers obsolete finding data suit updated goals scopes; conducting assessment affected least possible uncertainty. Following theoretical overview principles binds LCA, authors want provide review completely view than state-of-the-art on how effectively interact other order more holistic system/process assessed. fascinating circumstance emerges any exergy approach would effective if joined (not replaced) because turned out complementary. This theory has long been developed many their case studies confirmation what Gutowski wrote years ago: no single criteria or subsidiary model, independently well aggregated, may offer suitable answer all conditions. Specifically, through review, practitioners able choose best suited methodology, according aims, join outcomes together achieve transdisciplinary knowledge behavior study system, design improvement strategies.

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