当前位置: X-MOL 学术J. Process Control › 论文详情
Modular Design Optimization using Machine Learning-based Flexibility Analysis
Journal of Process Control ( IF 3.316 ) Pub Date : 2020-05-06 , DOI: 10.1016/j.jprocont.2020.03.014
Atharv Bhosekar; Marianthi Ierapetritou

Recent studies on modular and distributed manufacturing have introduced a new angle to the traditional economies of scale that claim that large plants exhibit better efficiencies and lower costs. A modular design has several advantages, including higher flexibility of decisions, lower investment costs, shorter time-to-market, and adaptability to market conditions. While design flexibility is a widely studied concept in the process design, modular design provides an interesting new opportunity to the design optimization problem under demand variability. In this work, a framework for modular design under demand variability is proposed. The framework consists of two steps. First, the feasible region for each module is represented analytically with the help of the historical data or the data from a simulation using a classification technique. In the second step, the optimal design choice is obtained by integrating the classifier models built in the first step as constraints in the design optimization problem. The design optimization problem is first solved considering a single objective, i.e., minimizing the total cost or maximizing the flexibility. These two objectives are then addressed simultaneously using a multiobjective optimization framework that considers the tradeoff between maximizing the flexibility of design and minimizing the cost. Computational studies conducted using a case study of an air separation plant, demonstrate the efficacy of the proposed framework. Several advantages of using a modular design, as well as data-driven methods in the decision-making process in the design step, are discussed.
更新日期:2020-05-06

 

全部期刊列表>>
智控未来
聚焦商业经济政治法律
跟Nature、Science文章学绘图
控制与机器人
招募海内外科研人才,上自然官网
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
x-mol收录
湖南大学化学化工学院刘松
上海有机所
李旸
南方科技大学
西湖大学
伊利诺伊大学香槟分校
徐明华
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug