(209a) Towards a Comprehensive Decision-Support Framework for Sustainable Manufacturing
AIChE Annual Meeting
Monday, November 11, 2019 - 3:30pm to 3:55pm
To provide a fundamental definition for sustainability, we defined the sustainability as vector function . Using this definition, the sustainability status of a system and its transition toward sustainability can be measured, monitored, and interpreted. As sustainability is a continuous process, we formulated the problem as a multi stage decision problem in . To achieve the sustainability goals, we formulated the sustainability problem as a multi-objective control problem and proposed a decision support system in  with focusing more on tactical layer.
In this paper, we propose a new comprehensive decision support framework for manufacturing sustainability enhancement that is an extension to our recent work in . This two-layer (strategic and tactical) framework is designed based on the sustainability fundamentals and control theory. The two layer that are executed at different time scales are integrated to implement sustainability development strategies successfully. A model predictive control (MPC) strategy is used at the strategic control layer to find and update optimal sustainability strategic plans continuously (e.g. at each year) for archiving short-to-long term sustainability goals with considering external information changes (e.g. new regulations, supplies and demands) provided by external monitoring component and internal information provided by sustainability assessor at the tactical layer. The tactical layer, on the other hand, is responsible for implementing sustainability strategic plans successfully by minimizing the projectsâ implementation costs and time. The components of each layer, implementation mechanism, and methods are presented. The proposed framework provides a structured step-by-step guide to industry for achieving economic, environmental, and social sustainability goals with considering uncertainties related to external and internal parameters that affect the business. A case study on biodiesel manufacturing is illustrated to demonstrate methodological efficacy.
Moradi-Aliabadi, M. and Y. Huang, "Vector-Based Sustainability Analytics: A Methodological Study on System Transition toward Sustainability," Industrial and Engineering Chemistry Research, 55(12), 3239-3252, 2016.
 Moradi-Aliabadi, M. and Y. Huang, "Multistage Optimization for Chemical Process Sustainability Enhancement under Uncertainty," ACS Sustainable Chemistry and Engineering, 4(11), 6133-6143, 2016.
 Moradi-Aliabadi, M. and Y. Huang, âDecision Support for Enhancement of Manufacturing Sustainability: A Hierarchical Control Approach,â ACS Sustainable Chem. Eng., 6(4), 4809â4820, 2018.
* All correspondence should be addressed to Prof. Yinlun Huang (Phone: 313-577-3771; E-mail: email@example.com).