Julia Reisinger, Maria Antonia Zahlbruckner, Iva Kovacic, Peter Kán, Xi Wang-Sukalia, Hannes Kaufmann
Integrated multi-objective evolutionary optimization of production layout scenarios for parametric structural design of flexible industrial buildings
Journal of Building Engineering, 46:1-18, 2021.

Information

  • Publication Type: Journal Paper (without talk)
  • Workgroup(s)/Project(s): not specified
  • Date: 2021
  • DOI: 10.1016/j.jobe.2021.103766
  • Journal: Journal of Building Engineering
  • Pages (from): 1
  • Pages (to): 18
  • Volume: 46
  • Keywords: Parametric modelling, Multi-objective optimization, Layout planning, Automated production layout generation, Evolutionary algorithm, Integrated industrial building design

Abstract

Due to product individualization, customization and rapid technological advances in manufacturing, 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 planning and structural building design are mostly sequential and the data and models lack interoperability. In this paper, a novel parametric evolutionary design method for automated production layout generation and optimization (PLGO) is presented, producing layout scenarios to be respected 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 constraints and objectives. Results suggest that our framework can produce feasible production layout 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 selection of several prioritized production layouts.

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BibTeX

@article{Reisinger-2021-JOBE,
  title =      "Integrated multi-objective evolutionary optimization of
               production layout scenarios for parametric structural design
               of flexible industrial buildings",
  author =     "Julia Reisinger and Maria Antonia Zahlbruckner and Iva
               Kovacic and Peter K\'{a}n and Xi Wang-Sukalia and Hannes
               Kaufmann",
  year =       "2021",
  abstract =   "Due to product individualization, customization and rapid
               technological advances in manufacturing, 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 planning and structural
               building design are mostly sequential and the data and
               models lack interoperability. In this paper, a novel
               parametric evolutionary design method for automated
               production layout generation and optimization (PLGO) is
               presented, producing layout scenarios to be respected 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 constraints
               and objectives. Results suggest that our framework can
               produce feasible production layout 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 selection of several prioritized
               production layouts.",
  doi =        "10.1016/j.jobe.2021.103766",
  journal =    "Journal of Building Engineering",
  volume =     "46",
  pages =      "1--18",
  keywords =   "Parametric modelling, Multi-objective optimization, Layout
               planning, Automated production layout generation,
               Evolutionary algorithm, Integrated industrial building
               design",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2021/Reisinger-2021-JOBE/",
}