AI-Supported Process Optimization Framework for Building Life Cycle Assessment

Neriman Gül Çelebi; Ümit Arpacıoğlu

doi:10.30785/mbud.1884790

TR EN

Bina Yaşam Döngüsü Değerlendirmesi için Yapay Zekâ Destekli Süreç Optimizasyonu Çerçevesi

Abstract

Çevre yönetim aracı olarak yaşam döngüsü değerlendirmesi (LCA) yapı endüstrisinin çevre üzerindeki etkilerini sistematik ve bütünleşik olarak analiz eden önemli bir sistematiktir. Yapay zeka (AI) özellikle yapı endüstrisi ve çevresel performans arasındaki veri entegrasyonunu sağlamak amacıyla giderek daha fazla kullanılmaktadır. Ancak literatürdeki yapay zeka destekli LCA çalışmaları çoğunlukla çevresel etki göstergelerinin tahminlerine odaklanmaktadır. Çevresel etki değerlendirmesi için GaBi gibi kapsamlı ve güçlü yazılımlar mevcuttur. Bu açıdan, LCA süreçlerini destekleyecek ve optimize edecek yaklaşıma ihtiyaç vardır. Bu çalışma, yapay zeka destekli bir süreç optimizasyonuna odaklanmaktadır ve çalışmada AI destekli bir LCA metodolojisi önerilmektedir. LCA için GaBi thinkstep yazılımı kullanılmıştır. Süreç optimizasyonu yaklaşımıyla, GaBi’de elde edilen çevresel verilerin yapay zeka desteğiyle yapı ölçeğinde normalize edilmiş çevresel performans göstergelerine dönüştürülmesi hedeflenmiştir. Python yazılımı aracılığıyla, normalize edilmiş değerleri üretmek için bir iş akışı (kodlama) tanımlanmıştır. Önerilen metodoloji doğrultusunda alternatif strüktürel sistemler analiz edilmiştir. Literatürde süreç optimizasyonuna ilişkin çalışmalar sınırlıdır ve bu çalışma ile literatüre katkı sağlamak amaçlanmaktadır.

Keywords

Yaşam döngüsü değerlendirmesi, yapay zeka, yapay zeka destekli LCA, süreç optimizasyonu

AI-Supported Process Optimization Framework for Building Life Cycle Assessment

Abstract

Life cycle assessment (LCA) as an environmental management tool is a crucial systematic that analyzes the environmental impacts of the construction industry in a systematic and integrated manner. Artificial intelligence (AI) is increasingly being used, particularly to facilitate data integration between the construction industry and environmental performance. However, AI-supported LCA studies in the literature prodominantly focus on estimating environmental impact indicators. Comprehensive and powerful software such as GaBi is available for environmental impact assessment. In this respect, there is a need for an approach that will support and optimize LCA processes. This study focuses on AI-supported process optimization and proposes an AI-supported LCA methodology. GaBi thinkstep software was used for LCA. With the process optimization approach, the aim is to transform the environmental data obtained in GaBi into normalized environmental performance indicators at the building scale with the support of AI. A workflow (coding) to generate normalized values was defined using Python software. Alternative structural systems were analyzed in line with the proposed methodology. Studies on process optimization are limited in the literature, and this study aims to contribute to the literature.

Keywords

Life cycle assessment, artificial intelligence, ai-supported LCA, process optimization

Ethical Statement

The article complies with national and international research and publication ethics. Ethics committee approval was not required for the study.

References

Barbhuiya, S. & Das, B. B. (2023). Life Cycle Assessment of construction materials: Methodologies, applications and future directions for sustainable decision-making. Case Studies in Construction Materials, 19. Doi: https://doi.org/10.1016/J.CSCM.2023.E02326
de Jesus, J. O., Oliveira-Esquerre, K. & Medeiros, D. L. (2021). Integration of artificial intelligence and life cycle assessment methods. IOP Conference Series: Materials Science and Engineering, 1196 (1). Doi: https://doi.org/10.1088/1757-899X/1196/1/012028
de Paula Salgado, I., Conrad, F., Signorini, C., Günther, E., Ihlenfeldt, S. & Mechtcherine, V. (2025). Integrating life cycle assessment (LCA) and machine learning for sustainable designs: a case study on protective layers made of mineral-bonded fiber-reinforced composites. The International Journal of Life Cycle Assessment, 30:11, 2403–2422. Doi: https://doi.org/10.1007/S11367-025-02454-7
European Committee for Standardization. (2011). Sustainability of construction works—Assessment of environmental performance of buildings—Calculation method, Brussels (Standard No. EN 15978:2011).
França, W. T., Barros, M. V., Salvador, R., de Francisco, A. C., Moreira, M. T. & Piekarski, C. M. (2021). Integrating life cycle assessment and life cycle cost: a review of environmental-economic studies. The International Journal of Life Cycle Assessment, 26(2), 244–274. Doi: https://doi.org/10.1007/s11367-020-01857-y
Gachkar, D., Gachkar, S., Ghofrani, E., García Martínez, A. & Angulo Bahón, C. (2025). Automating data integration for construction Life Cycle Assessment Using fuzzy matching and supervised learning. Automation in Construction, 178. Doi: https://doi.org/10.1016/J.AUTCON.2025.106381
Gong, J., Wilkinson, S. & Vishnupriya, V. (2025). Life cycle assessment software unveiled: exploring features and functions. The International Journal of Life Cycle Assessment, 30, 2446–2469. Doi: https://doi.org/10.1007/s11367-025-02557-1
IEA, ANNEX 57. (2016). Evaluation of Embodied Energy and CO2eq for Building Construction (Annex 57). Access Address (01.01.2026): https://www.iea-ebc.org/projects/project?AnnexID=57
International Organization for Standardization. (2006). ISO 14044: Environmental management—Life cycle assessment—Requirements and guidelines. Geneva, Switzerland.
Kim, S., Moon, J. H., Shin, Y., Kim, G. H. & Seo, D. S. (2013). Life comparative analysis of energy consumption and CO2 emissions of different building structural frame types. The Scientific World Journal. Doi: https://doi.org/10.1155/2013/175702

Kumar, D., Maurya, K. K., Mandal, S. K., Mir, B. A., Nurdiawati, A. & Al-Ghamdi, S. G. (2025). Life cycle assessment in the early design phase of buildings: strategies, tools, and future directions. Buildings, 15(10), 1612. Doi: https://doi.org/10.3390/BUILDINGS15101612/S1
Lasvaux, S., Habert, G., Peuportier, B. & Chevalier, J. (2015). Comparison of generic and product-specific Life Cycle Assessment databases: application to construction materials used in building LCA studies. The International Journal of Life Cycle Assessment, 20(11), 1473–1490. Doi: https://doi.org/10.1007/s11367-015-0938- z
Lechner, N. (2015). Heating, cooling, lighting: Sustainable design methods for architects (4th ed.). Hoboken, NJ: John Wiley & Sons.
Neupane, B., Belkadi, F., Formentini, M., Rozière, E., Hilloulin, B., Abdolmaleki, S. F. & Mensah, M. (2025). Machine learning algorithms for supporting life cycle assessment studies: An analytical review. Sustainable Production and Consumption, 56, 37–53. Doi: https://doi.org/10.1016/J.SPC.2025.03.015
Oladazimi, A., Mansour, S. & Hosseinijou, S. A. (2020). Comparative life cycle assessment of steel and concrete construction frames: A case study of two residential buildings in Iran. Buildings, Vol. 10, Page 54, 10(3). Doi: https://doi.org/10.3390/BUILDINGS10030054
Romeiko, X. X., Zhang, X., Pang, Y., Gao, F., Xu, M., Lin, S. & Babbitt, C. (2024). A review of machine learning applications in life cycle assessment studies. Science of The Total Environment, 912. Doi: https://doi.org/10.1016/J.SCITOTENV.2023.168969
Sphera. (n.d.). Life Cycle Assessment (LCA) Software. Access Address (01.01.2025): https://sphera.com/product-stewardship/life-cycle-assessment-software-and-data/?nab=1
Stek, E., Delong, D., McDonnell, T. & Rodriguez, J. (2011). Life Cycle Assessment Using ATHENA Impact Estimator for Buildings: A Case Study. Structures Congress 2011-Proceedings of the 2011 Structures Congress, 483–494. https://doi.org/10.1061/41171(401)42
Xu, M., Cai, H. & Liang, S. (2015). Big data and ındustrial ecology. Journal of Industrial Ecology, 19(2), 205–210. Doi: https://doi.org/10.1111/JIEC.12241

Details

Primary Language

English

Subjects

Sustainable Architecture

Journal Section

Research Article

Authors

Neriman Gül Çelebi ^*
0000-0003-0478-0449
Türkiye

Ümit Arpacıoğlu
0000-0001-8858-7499
Türkiye

Publication Date

July 28, 2026

Submission Date

February 8, 2026

Acceptance Date

July 6, 2026

Published in Issue

Year 2026 Volume: 11 Number: 1

DOI

https://doi.org/10.30785/mbud.1884790

IZ

https://izlik.org/JA86XJ37LS

APA

Çelebi, N. G., & Arpacıoğlu, Ü. (2026). AI-Supported Process Optimization Framework for Building Life Cycle Assessment. Journal of Architectural Sciences and Applications, 11(1), 439-448. https://doi.org/10.30785/mbud.1884790

AMA

1.Çelebi NG, Arpacıoğlu Ü. AI-Supported Process Optimization Framework for Building Life Cycle Assessment. JASA. 2026;11(1):439-448. doi:10.30785/mbud.1884790

Chicago

Çelebi, Neriman Gül, and Ümit Arpacıoğlu. 2026. “AI-Supported Process Optimization Framework for Building Life Cycle Assessment”. Journal of Architectural Sciences and Applications 11 (1): 439-48. https://doi.org/10.30785/mbud.1884790.

EndNote

Çelebi NG, Arpacıoğlu Ü (July 1, 2026) AI-Supported Process Optimization Framework for Building Life Cycle Assessment. Journal of Architectural Sciences and Applications 11 1 439–448.

IEEE

[1]N. G. Çelebi and Ü. Arpacıoğlu, “AI-Supported Process Optimization Framework for Building Life Cycle Assessment”, JASA, vol. 11, no. 1, pp. 439–448, July 2026, doi: 10.30785/mbud.1884790.

ISNAD

Çelebi, Neriman Gül - Arpacıoğlu, Ümit. “AI-Supported Process Optimization Framework for Building Life Cycle Assessment”. Journal of Architectural Sciences and Applications 11/1 (July 1, 2026): 439-448. https://doi.org/10.30785/mbud.1884790.

JAMA

1.Çelebi NG, Arpacıoğlu Ü. AI-Supported Process Optimization Framework for Building Life Cycle Assessment. JASA. 2026;11:439–448.

MLA

Çelebi, Neriman Gül, and Ümit Arpacıoğlu. “AI-Supported Process Optimization Framework for Building Life Cycle Assessment”. Journal of Architectural Sciences and Applications, vol. 11, no. 1, July 2026, pp. 439-48, doi:10.30785/mbud.1884790.

Vancouver

1.Neriman Gül Çelebi, Ümit Arpacıoğlu. AI-Supported Process Optimization Framework for Building Life Cycle Assessment. JASA. 2026 Jul. 1;11(1):439-48. doi:10.30785/mbud.1884790

AI-Supported Process Optimization Framework for Building Life Cycle Assessment

Bina Yaşam Döngüsü Değerlendirmesi için Yapay Zekâ Destekli Süreç Optimizasyonu Çerçevesi

Abstract

Keywords

AI-Supported Process Optimization Framework for Building Life Cycle Assessment

Abstract

Keywords

Ethical Statement

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

JASA JOURNAL TAG / MBUD DERGİ KÜNYESİ