Computational workflow integrating differential growth and robotic WAAM for fabrication-aware architectural design: a furniture-scale demonstrator

Purpose This study develops a fabrication-aware computational workflow for architectural applications using Wire-and-Arc Additive Manufacturing (WAAM). It addresses the gap in methods that integrate computational geometry with fabrication constraints, aiming to produce geometries that are both generative and manufacturable. The research formalizes a parameter-driven design-to-fabrication framework bridging computational modeling and robotic metal deposition, providing a transferable methodology that can inform applications beyond prototype-scale fabrication while preserving architectural design intent. Design/methodology/approach A computational workflow using differential growth principles in Grasshopper generates iterative geometries evaluated against fabrication criteria such as deposition stability, curvature continuity and robotic feasibility. Contour segmentation and toolpath simulation are incorporated as active design considerations rather than post-design checks. Designs are iteratively filtered and prepared for WAAM fabrication. The workflow is demonstrated through the production of an aluminum prototype, illustrating the translation of computational models into robotic metal deposition while embedding manufacturing constraints within the design-to-fabrication process. Findings The workflow integrates fabrication constraints within computational geometry generation, producing geometries that were assessed as both expressive and manufacturable. The WAAM-printed aluminum prototype demonstrates the practical translation of digital models into robotic deposition, with deposition continuity and self-supporting behavior observed during fabrication and inspection. Iterative evaluation supported geometry selection while maintaining generative flexibility. The study establishes a structured, parameter-driven design-to-fabrication workflow and identifies requirements for further quantitative validation and larger-scale architectural applications. Research limitations/implications The study is demonstrated through a furniture-scale prototype and does not include quantitative mechanical testing, comparative performance benchmarking or architectural-scale validation. Future research should investigate structural performance, process monitoring, thermal management, robotic reach, assembly interfaces and scalability for architectural applications. Practical implications The proposed workflow provides a structured approach for designers and researchers to consider fabrication constraints during computational geometry development rather than only after design completion. Iterative geometry filtering and toolpath simulation can help identify potential fabrication issues before physical production. The demonstrated furniture-scale application provides a practical basis for exploring similar workflows for customized metal components and architectural elements, while larger-scale implementation would require additional structural, robotic, thermal, logistical and economic evaluation. Originality/value This study embeds fabrication constraints directly within generative geometry, integrating differential growth with WAAM to establish a structured, parameter-driven design-to-fabrication workflow. The physical fabrication of an aluminum prototype demonstrates the translation of computational geometry into robotic metal deposition under fabrication constraints. The contribution lies in formalizing a reusable workflow that connects generative design, fabrication-aware filtering, toolpath preparation and robotic fabrication, while identifying a methodological basis for future investigation of larger-scale architectural applications.

Authors

Institutions

Publication Details

Journal
Engineering Computations
Published
2026-11-03
DOI
https://doi.org/10.1108/ec-03-2026-0429
Primary Topic
Architecture and Computational Design
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computational workflow integrating differential growth and robotic WAAM for fabrication-aware architectural design: a furniture-scale demonstrator

Ahmed Nasr, Rowan Elselmy
Engineering Computations
Architecture and Computational Design
article

Computational workflow integrating differential growth and robotic WAAM for fabrication-aware architectural design: a furniture-scale demonstrator

Ahmed Nasr, Rowan Elselmy
article en

Abstract

Purpose This study develops a fabrication-aware computational workflow for architectural applications using Wire-and-Arc Additive Manufacturing (WAAM). It addresses the gap in methods that integrate computational geometry with fabrication constraints, aiming to produce geometries that are both generative and manufacturable. The research formalizes a parameter-driven design-to-fabrication framework bridging computational modeling and robotic metal deposition, providing a transferable methodology that can inform applications beyond prototype-scale fabrication while preserving architectural design intent. Design/methodology/approach A computational workflow using differential growth principles in Grasshopper generates iterative geometries evaluated against fabrication criteria such as deposition stability, curvature continuity and robotic feasibility. Contour segmentation and toolpath simulation are incorporated as active design considerations rather than post-design checks. Designs are iteratively filtered and prepared for WAAM fabrication. The workflow is demonstrated through the production of an aluminum prototype, illustrating the translation of computational models into robotic metal deposition while embedding manufacturing constraints within the design-to-fabrication process. Findings The workflow integrates fabrication constraints within computational geometry generation, producing geometries that were assessed as both expressive and manufacturable. The WAAM-printed aluminum prototype demonstrates the practical translation of digital models into robotic deposition, with deposition continuity and self-supporting behavior observed during fabrication and inspection. Iterative evaluation supported geometry selection while maintaining generative flexibility. The study establishes a structured, parameter-driven design-to-fabrication workflow and identifies requirements for further quantitative validation and larger-scale architectural applications. Research limitations/implications The study is demonstrated through a furniture-scale prototype and does not include quantitative mechanical testing, comparative performance benchmarking or architectural-scale validation. Future research should investigate structural performance, process monitoring, thermal management, robotic reach, assembly interfaces and scalability for architectural applications. Practical implications The proposed workflow provides a structured approach for designers and researchers to consider fabrication constraints during computational geometry development rather than only after design completion. Iterative geometry filtering and toolpath simulation can help identify potential fabrication issues before physical production. The demonstrated furniture-scale application provides a practical basis for exploring similar workflows for customized metal components and architectural elements, while larger-scale implementation would require additional structural, robotic, thermal, logistical and economic evaluation. Originality/value This study embeds fabrication constraints directly within generative geometry, integrating differential growth with WAAM to establish a structured, parameter-driven design-to-fabrication workflow. The physical fabrication of an aluminum prototype demonstrates the translation of computational geometry into robotic metal deposition under fabrication constraints. The contribution lies in formalizing a reusable workflow that connects generative design, fabrication-aware filtering, toolpath preparation and robotic fabrication, while identifying a methodological basis for future investigation of larger-scale architectural applications.

Engineering Computations
Arab Academy for Science, Technology, and Maritime Transport (EG)
Openalex Percentile: Top 4%
Architecture and Computational Design
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon