Subproject SPP 2187 – The digital twin for fast and precise production of concrete modules

The project "The digital twin for fast and precise production of concrete modules" has its focus on the creation of a complete, consistent and up-to-date model representation of the various phases and aspects of the BIM process.

Prof. Markus König, Ruhr-University Bochum, Institute for Computing in Engineering, Germany
Prof. Detlef Gerhard, Ruhr-University Bochum, Institute for Digital Engineering, Germany

In the context of this project, a concrete module is defined as an individual construction member with physical interfaces to neighbouring parts of the structure or the surrounding environment. BIM (Building Information Modelling) is considered an information management method for construction projects based on the consistent use of digital models for the evaluation of the entire life cycle of the structure [1]. This consistency is essential for an efficient overall process chain in the sense of industrialized production based on Industry 4.0 concepts and CPPS (cyber-physical production systems) [2] from mechanical engineering.

The digital twin [3] as digital real-time representation of product, process and resources, functions essentially as a hub for all data analysis and visualization tools as well as for the control of industrial production lines. Among other aspects, the projects evaluates how data for the digital twin of a concrete module can be structured and connected, how functional requirements for production can formally and verifiably be modelled, how the individual modules can automatically collect important information for the production processes and interact with the production resources and processes, and how quality assurance for the individual modules can be improved based on the collected data.

The work programme initially includes the development of ontologies for various aspects of the overall process for modules made of freely mouldable high-performance materials. Particular aspects to be considered include construction, function, production, quality, service life duration, and recyclability. An agile and adaptive process requires continuous management of the requirements in line with Smart Engineering and corresponding traceability. For this purpose, the research includes the formal description of tolerances and domain-specific quality characteristics as well as the development of regular language for automatic testing (tracking and tracing). The development of the management shell according to RAMI 4.0 [4] is an essential work package.

Another essential work package consists in interaction models, in particular integration of existing data models of the construction industry with the management shell, in order to enable a holistic view of the planning and production of a building and the development of human-machine and machine-machine communication including semantic languages for the exchange of information. At the end of the project, basic concepts for the visualization and navigation of the digital twin and its interactions are developed based on the preceding tasks, using technologies from the field of virtual and augmented reality for human-machine interaction. At the end of the project, the methods and models that have been developed or implemented (based on prototypes) in the framework of Subproject SPP 2187 will be evaluated.
 

Subproject SPP 2187
A simulation-based method for evaluation of strategies for subdivision of construction systems into individual modules

This article introduces the development of a simulation-based method for evaluation of strategies for subdivision of construction systems into individual modules. Production technological aspects in the early development phases of the element or modular construction system are considered.

Madlin Müller, Prof.  Michael Völker and Prof. Thorsten Schmidt, Institute for Technical Logistic and Work Systems, TU Dresden, Germany

There exist a variety of equivalent variations for the structural design of high-performance concrete structures and the subdivision of the structure into individual modules, following the top-down process. In this context, a concrete module is defined as an individual construction member with physical interfaces to neighbouring parts of the structure or the surrounding environment. Variations to consider with respect to the structural form include reinforcement details, slab thickness, etc. From a manufacturing point of view, different production processes can be used to produce modules with approximately the same quality. Numerous possibilities exist for production process design and production organization in order to manufacture cost-optimized modules with high production efficiency.

This results in almost unlimited variations for the realization of the structure with regards to structural form and production technology. Due to the degree of freedom for the subdivision of the structure, the diversity of variants in relation to structural form is higher and more heterogeneous, in comparison to other industries. While, for example, in the automotive industry, the variants for final product subdivision are geometrically pre-defined by the functions of the individual parts, there are almost unlimited geometric variants when sub-dividing a high-performance concrete structure. The number of variants as input parameters for the definition of basic modules for the development of modular construction systems is in comparison significantly higher.

A pre-selection of the subdivision strategies must be made, and relevant restrictions have to be identified in order to evaluate if a module is suitable for the modular construction system. To this end, the evaluation of individual module variants is necessary from a production-technological point of view. Currently, it is not possible to efficiently evaluate the subdivision variants with predicted module quantities from a production-technical or process-organizational point of view, considering that the underlying aim is to achieve a high production output at low unit costs. In addition, there exist currently no specific design guidelines for high-performance concrete components from a production point of view.

The development goal is therefore a method for the holistic evaluation and pre-selection of subdivision strategies and technologies for high-performance concrete structures in the early development phases of the modular construction system. From a production perspective, the selection of suitable strategies results in a high potential for reducing the waste of resources.

Due to the high number of variants and complex interactions between the module, manufacturing process and process organization, as well as due to the influence of uncertain parameters, simulation-based optimization should be used as a methodological approach for the evaluation of different variants for the optimal production system. For this purpose, technology- or process-relevant production system blocks must be defined, and any production system variants must be configured as simulation models by means of parameter-based model generation. In order to reduce the simulation effort, simulation data is to be converted into machine learning models, to enable the development of proposals for basic module design and unit cost prediction for similar structures (Fig. 2).

In the early development phase of the basic module or modular system, only rough module properties and process parameters are known. Therefore, an abstraction level is to be chosen, with which sufficiently precise information can be obtained in order to meet the target performance characteristics with a particular subdivision variant. Furthermore, the aim is to determine restrictions of the modular subdivision process based on considerations related to manufacturing processes and process organization. As a consequence, holistic optimization takes place through iteration processes and generally applicable design guidelines are derived supported by machine learning methods.

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References

[1]Borrmann A., König M., Koch C., Beetz J. (2018) Building Information Modeling: Why? What? How?. In: Borrmann A., König M., Koch C., Beetz J. (Hg.) Building Information Modeling. Cham. Springer International Publishing, S. 1–24
[2]Biffl, S.; Gerhard, D.; Lüder, A (2017): Introduction to the Multi-Disciplinary Engineering for Cyber-Physical Production Systems. In: Biffl, Gerhard und Lüder (Hg.): Multi-Disciplinary Engineering for Cyber-Physical Production Systems. data models and software solutions for handling complex engineering projects, Bd. 94. Cham: Springer International Publishing, S. 1–24
[3]Gerhard, Detlef (2020): Digital Engineering – Basis für Smarte Produkte und Services. In: M. Steven und J. N. Dörseln (Hg.): Smart Factory: Einsatzfaktoren - Technologie - Produkte: Kohlhammer Verlag, S. 21-34
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