Integrated multi-objective evolutionary optimization of production layout scenarios for parametric structural design of flexible industrial buildings

被引:12
|
作者
Reisinger, Julia [1 ]
Zahlbruckner, Maria Antonia [1 ]
Kovacic, Iva [1 ]
Kan, Peter [2 ]
Wang-Sukalia, Xi [2 ]
Kaufmann, Hannes [2 ]
机构
[1] Vienna Univ Technol, Inst Interdisciplinary Construct Proc Management, Dept Integrated Planning & Ind Bldg, Karlspl 13,E234-02, A-1040 Vienna, Austria
[2] Vienna Univ Technol, Inst Visual Comp & Human Centered Technol, Favoritenstr 9,E193, A-1040 Vienna, Austria
来源
关键词
Parametric modelling; Multi-objective optimization; Layout planning; Automated production layout generation; Evolutionary algorithm; Integrated industrial building design; GENETIC ALGORITHM; SPACE LAYOUT; FACILITY; PERFORMANCE; MODEL; CONSTRUCTION; ARCHITECTURE; ENVIRONMENT; SIMULATION; SUPPORT;
D O I
10.1016/j.jobe.2021.103766
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Due to product individualization, customization and rapid technological advances in manufac-turing, production systems are faced with frequent reconfiguration and expansion. Industrial buildings that allow changing production scenarios require flexible load-bearing structures and a coherent planning of the production layout and building systems. Yet, current production plan-ning and structural building design are mostly sequential and the data and models lack interoper-ability. In this paper, a novel parametric evolutionary design method for automated production layout generation and optimization (PLGO) is presented, producing layout scenarios to be re-spected in structural building design. Results of a state-of-the-art analysis and a case study are combined to develop a novel concept of integrated production cubes and the design space for PLGO as basis for a parametric production layout design method. The integrated production cubes concept is then translated into a parametric PLGO framework, which is tested on a pilot-project of a hygiene production facility to evaluate the framework and validate the defined con-straints and objectives. Results suggest that our framework can produce feasible production lay-out scenarios, which respect flexibility and building requirements. In future research the design process will be extended by the development of a multi-objective evolutionary optimization process for industrial buildings to provide flexible building solutions that can accommodate a se-lection of several prioritized production layouts.
引用
收藏
页数:18
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