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ERIC Number: ED558995
Record Type: Non-Journal
Publication Date: 2013
Pages: 210
Abstractor: As Provided
Reference Count: N/A
ISBN: 978-1-3032-8484-7
Decision Guidance for Sustainable Manufacturing
Shao, Guodong
ProQuest LLC, Ph.D. Dissertation, George Mason University
Sustainable manufacturing has significant impacts 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 dissertation developed the Sustainable Process Description and Analytics (SPDA) formalism and a systematic decision guidance methodology to fill the research gaps. The methodology provides step-by-step guidance for sustainability performance analysis and decision optimization using the SPDA formalism. The SPDA formalism supports unified syntax and semantics for querying, what-if analysis, and decision optimization; enables modular, extensible, and reusable modeling; enables built-in process and sustainability metrics modeling that allows users using data from production, energy management, life cycle assessment reference database for modeling and analysis; and is easy to use by manufacturing and business users. Reduction procedures are developed to enable the translations of the SPDA query into specialized models such as optimization or simulation model for decision guidance. Two sustainable manufacturing case studies have been performed to demonstrate the use of formalism and the methodology. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page:]
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Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A