A decision-guidance framework for sustainability performance analysis of manufacturing processes
- Authors
- Kim, Duck Bong; Shin, Seung Jun; Shao, Guodong; Brodsky, Alexander
- Issue Date
- Jan-2015
- Publisher
- SPRINGER LONDON LTD
- Keywords
- Decision support and guidance; Machining process; Manufacturing processes; Sustainability performance analysis; Sustainable manufacturing
- Citation
- INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, v.78, no.9-12, pp.1455 - 1471
- Indexed
- SCIE
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Volume
- 78
- Number
- 9-12
- Start Page
- 1455
- End Page
- 1471
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/158049
- DOI
- 10.1007/s00170-014-6711-9
- ISSN
- 0268-3768
- Abstract
- Life cycle assessment (LCA) frameworks are widely used to assess the sustainability of manufacturing processes. Although they have several advantages such as systematic estimation and efficiency, they have significant limitations due to a lack of functionality to perform sustainability analysis. Specifically, they do not fully support dynamic and diverse characteristics of manufacturing processes nor cover technical details for the further analysis, such as simulation, prediction, and optimization. In addition, they do not provide a unified modeling environment in which to perform various sustainability analysis tasks. In this paper, a decision-guidance framework has been presented to improve sustainability in manufacturing processes while addressing the deficiencies in existing LCA frameworks. The proposed framework consists of six phases: goal and scope definition, data collection, model generation, sustainability performance analysis, interpretation, and decision support and guidance, which is designed in terms of functionality, usability, flexibility/reusability, and interoperability. To demonstrate the use of the framework, a case study of a turning process has been performed.
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