Decision guidance methodology for sustainable manufacturing using process analytics formalism
- Authors
- Shao, Guodong; Brodsky, Alexander; Shin, Seungjun; Kim, Duck Bong
- Issue Date
- Nov-2014
- Publisher
- SPRINGER
- Keywords
- Decision guidance; Energy consumption; Optimization; Process analytics; Sustainable manufacturing
- Citation
- JOURNAL OF INTELLIGENT MANUFACTURING, v.28, no.02, pp.455 - 472
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF INTELLIGENT MANUFACTURING
- Volume
- 28
- Number
- 02
- Start Page
- 455
- End Page
- 472
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/158632
- DOI
- 10.1007/s10845-014-0995-3
- ISSN
- 0956-5515
- Abstract
- Sustainable manufacturing has significant impact on a company's business performance and competitiveness in today's world. A growing number of manufacturing industries are initiating efforts to address sustainability issues; however, to achieve a higher level of sustainability, manufacturers need methodologies for formally describing, analyzing, evaluating, and optimizing sustainability performance metrics for manufacturing processes and systems. Currently, such methodologies are missing. This paper introduces a systematic decision-guidance methodology that uses the sustainable process analytics formalism (SPAF) developed at the National Institute of Standards and Technology. The methodology provides step-by-step guidance for users to perform sustainability performance analysis using SPAF, which supports data querying, what-if analysis, and decision optimization for sustainability metrics. Users use data from production, energy management, and a life cycle assessment reference database for modeling and analysis. As an example, a case study of investment planning for energy management systems has been performed to demonstrate the use of the methodology.
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