Identifying the Design Feature That Causes Project Delay in DfMA: A Dominant Element Analysis Method for Project Scheduling
Abstract
Design for manufacturing and assembly (DfMA) is an engineering methodology which aims to increase ease of manufacture and efficiency of assembly by considering manufacturing and assembly constraints in the design process. However, current DfMA approaches in the construction sector are not automated enough to identify the design features that may cause project delay in real time. This leads to longer design cycle. Also, current scheduling algorithms rely on human intervention to generate activity network from a design output. Addressing these inefficiencies, we propose an interpretative machining learning model to predict the construction duration given a design output. More importantly, the same model identifies the design features that may cause the most delay in the project. The model is trained on a residential design dataset with various features, such as layout, geometry, and element typology. The output of the model is the project duration and an importance map, indicating the influence each feature of the given design has on the total project duration. The results from this model can considerably reduce the design cycle by supporting architects to create fabrication and assembly aware design even when they have little knowledge of production and assembly processes. This model will contribute to a novel computational approach for DfMA. Show more
Publication status
publishedExternal links
Book title
Computing in Civil Engineering 2023: Visualization, Information Modeling, and SimulationPages / Article No.
Publisher
American Society of Civil EngineersEvent
Organisational unit
09566 - Dillenburger, Benjamin / Dillenburger, Benjamin
More
Show all metadata
ETH Bibliography
yes
Altmetrics