{"title":"Integration of BIM and robotic fabrication for sustainable design and manufacturing of free-form building façade panels in off-site construction","authors":"Amirhossein Mehdipoor, Walid Anane, Sahar Mehdipoorkaloorazi, Ivanka Iordanova","doi":"10.1007/s44150-025-00142-6","DOIUrl":null,"url":null,"abstract":"<div><p>The construction industry faces persistent challenges related to inefficiency, high energy consumption, and environmental impacts, necessitating innovative approaches to sustainable building practices. These challenges are further amplified in off-site construction (OSC) manufacturing of free-form components like façade panels, which demand extensive coordination, labor, and time due to their complex geometries and unique designs. This research addresses these issues by integrating Building Information Modeling (BIM) and robotic fabrication to develop a parametric methodology for optimizing façade designs in OSC. The methodology incorporates generative design to evaluate and select façade solutions based on minimizing solar radiation and façade area, while adhering to energy efficiency and sustainability criteria. A mock-up case study was used to validate the approach, utilizing BIM to generate a Building Energy Model (BEM) for energy performance analysis. The findings demonstrate significant reductions in solar radiation through the selected façade designs, highlighting the methodology’s potential to improve environmental performance. By incorporating digital fabrication and robotic manufacturing, the methodology mitigates the challenges of producing free-form components, streamlining production, reducing labor intensity, and enhancing accuracy. This research contributes a scalable framework for sustainable façade design and fabrication, advancing the efficiency and adaptability of OSC workflows.</p></div>","PeriodicalId":100117,"journal":{"name":"Architecture, Structures and Construction","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44150-025-00142-6.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Architecture, Structures and Construction","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s44150-025-00142-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The construction industry faces persistent challenges related to inefficiency, high energy consumption, and environmental impacts, necessitating innovative approaches to sustainable building practices. These challenges are further amplified in off-site construction (OSC) manufacturing of free-form components like façade panels, which demand extensive coordination, labor, and time due to their complex geometries and unique designs. This research addresses these issues by integrating Building Information Modeling (BIM) and robotic fabrication to develop a parametric methodology for optimizing façade designs in OSC. The methodology incorporates generative design to evaluate and select façade solutions based on minimizing solar radiation and façade area, while adhering to energy efficiency and sustainability criteria. A mock-up case study was used to validate the approach, utilizing BIM to generate a Building Energy Model (BEM) for energy performance analysis. The findings demonstrate significant reductions in solar radiation through the selected façade designs, highlighting the methodology’s potential to improve environmental performance. By incorporating digital fabrication and robotic manufacturing, the methodology mitigates the challenges of producing free-form components, streamlining production, reducing labor intensity, and enhancing accuracy. This research contributes a scalable framework for sustainable façade design and fabrication, advancing the efficiency and adaptability of OSC workflows.