Abstract
Most industrial buildings have a very short lifespan due to frequently changing production processes. The load-bearing structure severely limits the flexibility of industrial buildings and is a major contributor to their costs, carbon footprint and waste. This paper presents a parametric optimization and decision support (POD) model framework that enables automated structural analysis and simultaneous calculation of life cycle cost (LCC), life cycle assessment (LCA), recycling potential and flexibility assessment. A method for integrating production planning into early structural design extends the framework to consider the impact of changing production processes on the footprint of building structures already at an early design stage. With the introduction of a novel grading system, design teams can quickly compare the performance of different building variants to improve decision making. The POD model framework is tested by means of a variant study on a pilot project from a food and hygiene production facility. The results demonstrate the effectiveness of the framework for identifying potential economic and environmental savings, specifying alternative building materials, and finding low-impact industrial structures and enclosure variants. When comparing the examined building variants, significant differences in the LCC (63%), global warming potential (62%) and flexibility (55%) of the structural designs were identified. In future research, a multi-objective optimization algorithm will be implemented to automate the design search and thus improve the decision-making process.
Highlights
The construction industry is one of the key sectors for sustainable development, as buildings account for 30 to 40% of the primary energy use worldwide [1]
The results revealed that the initial construction cost of a green industrial building is 29% higher than that of a traditional building; in terms of life cycle cost (LCC), green industrial buildings are 17% cheaper than the traditional buildings
This paper presents the development of the parametric optimization and decision support (POD) model framework for automated integrated production planning and structural industrial building design, enabling performance feedback and visualization of the trade-off among LCC, life cycle assessment (LCA), recycling potential and flexibility assessment already at an early design stage
Summary
The construction industry is one of the key sectors for sustainable development, as buildings account for 30 to 40% of the primary energy use worldwide [1]. Industrial buildings produce many resources and waste [3], as they consume a huge amount of materials for foundations, load-bearing structures and the building envelope [4]. The employed building materials account for the highest percentage of the total embodied energy and carbon in industrial buildings [5]. Due to short product life cycles, industrial buildings have a relatively short service life, ranging from 15 to 30 years. In order to extend the life cycle of industrial buildings, building structures must be able to adapt to reconfiguring and expanding production processes, which is a challenge for structural design. Optimizing the load-bearing structure for flexibility and coupling of production planning models already in the early design stage can contribute to increase the economic and environmental sustainability of industrial buildings [7,8]. Often, structural design decisions enter the industrial building design process late and are subservient to architectural and production goals
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