A spatial superstructure approach to the optimal design of modular processes and supply chains
A spatial superstructure approach to the optimal design of modular processes and supply chains
复制标题
模块化流程和供应链优化设计的空间上层建筑方法
DOI:
10.1016/j.compchemeng.2022.108102
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发表时间:
2023
影响因子:
4.3
通讯作者:
Zavala, Victor M.
中科院分区:
文献类型:
--
作者:
Shao, Yue;Ma, Jiaze;Zavala, Victor M.
Modularity is a design principle that aims to provide flexibility for spatio-temporal assembly/disassembly and reconfiguration of systems. This design principle can be applied to multiscale (hierarchical) manufacturing systems that connect units, processes, facilities, and entire supply chains. Designing modular systems is challenging because of the need to capture spatial interdependencies that arise between system components due to product exchange/transport between components and due to product transformation in such components. In this work, we propose an optimization framework to facilitate the design of modular manufacturing systems. Central to our approach is the concept of a spatial superstructure, which is a graph that captures all possible system configurations and interdependencies between components. The spatial superstructure is a generalization of the notion of a superstructure and of a p-graph used in process design, in that it encodes spatial (geographical) context of the system components. We show that this generalization facilitates the simultaneous design and analysis of processes, facilities, and of supply chains. Our framework aims to select the system topology from the spatial superstructure that minimizes design cost and that maximizes design modularity. We show that this design problem can be cast as a mixed-integer, multi-objective optimization formulation. We demonstrate these capabilities using a case study arising in the design of a plastic waste upcycling supply chain.
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DOI:
10.1016/b978-0-12-818597-1.50041-2
发表时间:
2019
期刊:
Computer Aided Chemical Engineering
影响因子:
--
作者:
Qi Chen;I. Grossmann
通讯作者:
I. Grossmann
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
E. Pistikopoulos;Yuhe Tian;R. Bindlish
通讯作者:
R. Bindlish
影响因子:
--
作者:
Allen, R. Cory;Avraamidou, Styliani;Pistikopoulos, Efstratios N.
通讯作者:
Pistikopoulos, Efstratios N.
影响因子:
3.7
作者:
Atharv Bhosekar;Oluwadare Badejo;M. Ierapetritou
通讯作者:
M. Ierapetritou
影响因子:
8.3
作者:
Michel Berthélemy;L. Rangel
通讯作者:
L. Rangel