Digitalized composite material and product development – Strategies and methods for multiscale experimental-numerical validation processes using PLM and MBSE approaches
Topic(s) : Material and Structural Behavior - Simulation & Testing
Co-authors :
Jonas RICHTER (GERMANY), Maximilian Peter DAMMANN (GERMANY), Maximilian KLUGE , Bernhard SASKE , Stephan ARNDT (GERMANY), Andreas HORNIG (GERMANY), Kristin PAETZOLD-BYHAIN , Niels MODLERAbstract :
In recent years, engineering using innovative, lightweight, high-performance composite materials has gained significant attention in both scientific and various industrial sectors. This trend is driven by growing needs for enhanced energy efficiency and reduced emissions. Also, increasing importance of digitalization is evident to achieve these aims and optimize product and development (PD) process efficiency. Product Lifecycle Management (PLM) serves as a comprehensive strategy, managing products and their associated processes and information consistently throughout their lifecycle. Adhering to the FAIR principle (findable, accessible, interoperable, reusable) to store and manage data is crucial for productivity. In PD for composite materials the design, analysis and experimental-numerical validation/verification processes and the models are complex, interlinked and often highly iterative [1]. Additionally, various levels of the validation pyramid (coupon to full system) have to be considered. The Model-Based Systems Engineering (MBSE) describing and standardizing digital system models and data facilitates, improves and modifies processes [2]. Using linked digital models with data and information flows to map the system, MBSE provides a different perspective on PD data managed in PLM and significantly enhances the digital process efficiency.
This contribution examines methods for modeling the experimental-numerical validation process chain using PLM concepts to store and manage data and MBSE concepts to track data links and process steps. A process roadmap is elaborated, outlining key processes, subprocesses, and metadata for managing various data and procedures in PD processes for a hybrid composite structure consisting of steel sheet, GF-PA organo sheet, and injection molded rib structure. Then, an event-driven process chain is exemplarily set up, linking processes, inputs, outputs, software needs, and decision points that may cause iterations. Key processes and their metadata are used to create customizable, connectable blocks in the software Enterprise Architect (EA) to model and visualize process chains, using SYSml, a typical MBSE modeling language. The concepts and planned functionalities including requirement management are developed and examined based on highly heterogeneous data. With the PLM software Aras Innovator, used to manage digital data and their versioning, the simulation data is then categorized into studies, tasks, CAD/CAE models and evaluation data. The managed data can be accessed through an interface linked by respective metadata. As a result, a template to build procedural process chains using pre-configured building blocks in EA is elaborated. This enables customization, interlinking to suit individual needs and future automatic procedure suggestions based on data of previous projects. The approach highlights increased PD efficiency through data reuse, workflow execution, consistent data management and traceability.
This contribution examines methods for modeling the experimental-numerical validation process chain using PLM concepts to store and manage data and MBSE concepts to track data links and process steps. A process roadmap is elaborated, outlining key processes, subprocesses, and metadata for managing various data and procedures in PD processes for a hybrid composite structure consisting of steel sheet, GF-PA organo sheet, and injection molded rib structure. Then, an event-driven process chain is exemplarily set up, linking processes, inputs, outputs, software needs, and decision points that may cause iterations. Key processes and their metadata are used to create customizable, connectable blocks in the software Enterprise Architect (EA) to model and visualize process chains, using SYSml, a typical MBSE modeling language. The concepts and planned functionalities including requirement management are developed and examined based on highly heterogeneous data. With the PLM software Aras Innovator, used to manage digital data and their versioning, the simulation data is then categorized into studies, tasks, CAD/CAE models and evaluation data. The managed data can be accessed through an interface linked by respective metadata. As a result, a template to build procedural process chains using pre-configured building blocks in EA is elaborated. This enables customization, interlinking to suit individual needs and future automatic procedure suggestions based on data of previous projects. The approach highlights increased PD efficiency through data reuse, workflow execution, consistent data management and traceability.