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A Decision Guidance Framework for Sustainability Performance Analysis of Manufacturing Processes

Published

Author(s)

Duck B. Kim, Seungjun Shin, Guodong Shao, Alexander Brodsky

Abstract

Life-Cycle Assessment (LCA) methods are widely used to assess the sustainability of manufacturing processes. Although it has several advantages such as systematic estimation and efficiency, it has significant limitations due to lack of functionality to perform sustainability analysis. For example, it does not support decision optimization and parameter calibration. Additionally, it does 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 with addressing the deficiencies in LCA. 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.
Citation
International Journal of Advanced Manufacturing Technology

Keywords

Sustainable manufacturing, sustainability performance analysis, decision support and guidance, manufacturing processes, and machining process

Citation

Kim, D. , Shin, S. , Shao, G. and Brodsky, A. (2015), A Decision Guidance Framework for Sustainability Performance Analysis of Manufacturing Processes, International Journal of Advanced Manufacturing Technology (Accessed October 5, 2024)

Issues

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Created January 10, 2015, Updated February 19, 2017