<div class="csl-bib-body">
<div class="csl-entry">Reisinger, J., Knoll, M., & Kovacic, I. (2021). Design space exploration for flexibility assessment and decision making support in integrated industrial building design. <i>Optimization and Engineering</i>, <i>22</i>(3), 1693–1725. https://doi.org/10.1007/s11081-021-09614-2</div>
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dc.identifier.issn
1389-4420
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/137426
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dc.description.abstract
Industrial buildings play a major role in sustainable development, producing and expending a significant amount of resources, energy and waste. Due to product individualization and accelerating technological advances in manufacturing, industrial buildings strive for highly flexible building structures to accommodate constantly evolving production processes. However, common sustainability assessment tools do not respect flexibility metrics and manufacturing and building design processes run sequentially, neglecting discipline-specific interaction, leading to inflexible solutions. In integrated industrial building design (IIBD), incorporating manufacturing and building disciplines simultaneously, design teams are faced with the choice of multiple conflicting criteria and complex design decisions, opening up a huge design space. To address these issues, this paper presents a parametric design process for efficient design space exploration in IIBD. A state-of-the-art survey and multiple case study are conducted to define four novel flexibility metrics and to develop a unified design space, respecting both building and manufacturing requirements. Based on these results, a parametric design process for automated structural optimization and quantitative flexibility assessment is developed, guiding the decisionmaking process towards increased sustainability. The proposed framework is tested on a pilot-project of a food and hygiene production, evaluating the design space representation and validating the flexibility metrics. Results confirmed the efficiency of the process that an evolutionary multi-objective optimization algorithm can be implemented in future research to enable multidisciplinary design optimization for flexible industrial building solutions.
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dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.language.iso
en
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dc.publisher
SPRINGER
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dc.relation.ispartof
Optimization and Engineering
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Electrical and Electronic Engineering
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dc.subject
Software
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dc.subject
Mechanical Engineering
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dc.subject
Control and Optimization
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dc.subject
Civil and Structural Engineering
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dc.subject
Decision making
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dc.subject
Aerospace Engineering
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dc.subject
Design space exploration
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dc.subject
Parametric modeling
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dc.subject
Structural performance optimization
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dc.subject
Flexibility metrics
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dc.title
Design space exploration for flexibility assessment and decision making support in integrated industrial building design