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
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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.
Zavala, Victor M.
中科院分区:
工程技术2区
文献类型:
--
作者:
Shao, Yue;Ma, Jiaze;Zavala, Victor M.

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模块化是一种设计原则,旨在为系统的时空组装/拆卸和重新配置提供灵活性。这种设计原则可以应用于连接单元、流程、设施和整个供应链的多尺度(分层)制造系统。设计模块化系统具有挑战性,因为需要捕捉由于组件之间的产品交换/传输以及这些组件中的产品转换而产生的系统组件之间的空间相互依赖性。在这项工作中,我们提出了一个优化框架,以促进模块化制造系统的设计。我们方法的核心是空间上层结构的概念,它是一个图,捕获了所有可能的系统配置和组件之间的相互依赖关系。空间上层建筑是上层建筑和过程设计中使用的p图概念的概括,因为它编码了系统组件的空间(地理)背景。我们表明,这种概括有助于过程、设施和供应链的同时设计和分析。我们的框架旨在从空间上层结构中选择系统拓扑,使设计成本最小化,并使设计模块化最大化。我们表明,该设计问题可以转换为一个混合整数,多目标优化公式。我们通过塑料废物升级回收供应链设计中的案例研究来展示这些能力。
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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