Abstract:
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.
