Strategieberatung
Streamlined Modeling with Generative Building Blocks
The video clearly illustrates this advantage: whereas conventional manual construction of a road intersection is time-consuming and involves extensive detail work, using a generative simulation building block is significantly faster. Once established, these benefits continue to accumulate with each use, further accelerating model construction.
What is a “generative building block”?
Simulation models consist of two central components: the physical objects—such as workstations, buffers, warehouses, routes, or logistics vehicles—and the associated information structures, such as databases and program codes. Both elements can be customized individually. Parameterized objects or codes can be saved as templates and reused for new applications with minimal adjustment.
How is a generative building block modeled?
A workstation, for example, can be modeled in such a way that it decides independently and autonomously, regardless of its function, which transport process is triggered for a finished component: an unmanned transport vehicle or a conveyor belt. Both processes are based on the same template, but differ in their dynamically controlled process logic. The relevant information is maintained centrally in databases – no longer locally in each object. This has resulted in a generative building block: flexible, versatile, and reusable.
How can generative building blocks be managed for long-term sustainability?
If multiple building blocks are required, a “building block library” should be created. The library can be imported into a simulation model as a whole, and the building blocks it contains can be used as needed. It enables structured versioning, includes higher-level control, and provides interfaces between the building blocks. This creates a scalable, flexible, and future-proof simulation ecosystem.
Typical use cases are extensive greenfield or brownfield projects in which complex production or logistics systems are planned and simulated. As many projects have shown, this can reduce modeling effort by up to 50 percent—while simultaneously increasing model quality and reusability.
What requirements must a generative building block meet?
To achieve maximum cost and time savings, three key requirements must be met:
Reusability
through flexibility and modularity
- Building blocks are created in such a way that they can cover as many different use cases as possible. This is achieved through predefined functions and logic that can be called up as needed and customized using parameters.
- Parameterization is carried out via centralized and automated data management. This gives users direct access to all modules used and allows them to make adjustments via an interface.
Lean modeling
through standardization and organization
- The design of the modules is self-explanatory and offers an intuitive user interface that users can quickly navigate.
- A library implements uniform structure and design specifications in all modules, ideally derived from the corporate design/corporate identity.
- Clear structures enable every user to quickly get started with unfamiliar simulation models. This also makes it easier to validate the simulation models.
Accessibility
through intuitive operation
- Intuitive and self-explanatory applicability of the modules is a basic requirement and must be taken into account during development.
- Building blocks enable more efficient work through a division of labor: simulation experts develop the building blocks, while less experienced users or employees from other departments can use them to construct simulation models. These building blocks can also support the onboarding of new employees.
Future-Proof Through Generative Building Blocks
With generative simulation building blocks, you lay the foundation for a future-proof modeling strategy.
Whether you aim to integrate AI-supported optimizations, implement (partially) automated model structures, or connect your simulation model to an Industrial Metaverse in the future, a well-structured building block library provides maximum flexibility to meet upcoming challenges.
We are happy to support you in developing generative modules and setting up a simulation library. Please feel free to contact us.