amc trr 277 additive manufacturing in construction

Integrating Digital Design and Additive Manufacturing through BIM-Based Decision Support and Digital Twin Methods

The project will contribute to closing the gap between digital design and additive manufacturing. The conceived Design Decision Support System (DDSS) will enable the identification of components suitable for AM technology, founded on a for-mal AM knowledge base. Methods will be developed for generating Fabrication Information Models (FIM) from Building Information Models (BIM). These me-

thods will be based on graph theory and algorithmic geometry. By incorporating manufacturing information from robots and sensors, methods for creating digital twin representations reflecting as-built geometry and properties are developed. The approaches are based on the concept of multi-LOD BIM ensuring the consis-tency between multiple levels of detail.

Summary

AMC The Challenge of Large ScaleTRR 277 Additive Manufacturing in ConstructionTechnische Universität BraunschweigTechnical University of Munich

AMC The Challenge of Large ScaleAdditive Manufacturing in Construction

TRR 277

Prof. Dr.-Ing. André BorrmannProf. Dr.-Ing. Frank Petzold

Chair of Computational Modeling and Simulation, TUMChair of Architectural Informatics, TUM

Research QuestionsTo close the gap between digital design and additive manufacturing, the following questions are tackled:

• How can a knowledge-driven systems support architects and engineers to select suitable AM methods?

• How can the concept of multi-LOD BIM be extended to support Fabrication Information Models that contain detailed information about AM processes?

• How can Fabrication Information Models be automatically derived from BIM models?

• How can a digital twin representation for AM components be designed to integrate information from various sensors to provide detailed as-built models?

The proposed Design Decision Support System (DDSS) is founded on a knowledge base formalising the capabilities and boundary conditions of individual AM processes.

Multi-LOD BIM models allow for an adequate level of detail corresponding to the design progress. The project will investigate how FIM can be integra-ted and automatically derived from a detailed BIM model.

Methods• Development of a multi-scale geometric model

for AM in construction (with C01).• Combination of B-Rep and V-Rep as well as

semantic modelling for multi-LOD BIM.• Combination of graph transformation with

algorithmic geometry for automated FIM derivation.

• DDSS: Knowledge representation based on graph theory and ontological descriptions.

• Usability experiments with potential users for validating the DDSS methodology.

Preliminary Work• Long track record in BIM research, both on the

fundamental and on the application level. Long list of joint projects.

• Extensive background in design decision support for early design phases (Petzold).

• Introduction of multi-LOD BIM methods for tunnels and buildings (Borrmann).

• Extensive experience in knowledge representa-tion, graph rewriting, procedural geometry and parametric modeling.

The internal structure of a concrete component produced by AM (Chair of Timber Structures and Building Construction, TUM)

The conceived design decision support system will support architects and engineers in choosing suitable AM processes for realising organic buil-ding designs.

Right: Usage of FIM for steering the manufacturing process. Left: Different variants of FIM for one BIM element.

WP 3

WP 1.1Analysis of AM methods

WP 1.2Formal description of a knowledge base

WP 1.3Integration into a BIM system

WP 2.1Multi-LOD BIM: concept and datastructures

Digital Twin

WP 1.4Explanationfunctionalities

WP 2.2Automated derivation of fabrication information models

WP 3.1Digital Twin: Data Structures

WP 3.2Digital Twin:GeometryUpdate

WP 3.3Digital Twin:Process Data Integration

WP 4Validation

WP 1 Design Decision Support

WP 2 Fabrication-enhancedBIM models

BIM LOD1

BIM LOD2

FIM

BIM LOD3