SDM as information hub for the digital twin
Improve efficiency by automating simulations
End-to-end process chain from requirements to reporting
Establish traceable documentation (traceability, auditability)
Efficient introduction of SDM systems using proven 3-step plan
Digitalization is proceeding at high speed across all industries – including manufacturers who have up until now been developing predominantly mechanical products. This shift towards the development of mechatronic and cyber-physical products and systems presents them with new interdisciplinary challenges. There is a need to provide digital descriptions of physical products in their entirety and enable simulation of all functions in advance (digital twin), for example by shortening the time-to-market. This cannot be done without efficient management of the data belonging to the underlying digital models.
Simulation data management (SDM) systems are designed specifically for this purpose. They make it possible to establish an end-to-end process chain – from model design to simulation to reporting the results – and automate it to the greatest extent possible. The experience that :em AG has gained from the projects it has completed indicates that the introduction of SDM offers the potential to boost efficiency by 30% to 50%.
What we offer you
Does this sound familiar?
- You manage your simulation data in complex folder structures in the file system – data searches, versioning and change management involve significant manual effort.
- A lack of overarching model management (also across different locations) leads to redundant databases and the same models being created multiple times.
- The level of complexity brought about by the “mechatronization” of your products, and the interdisciplinary complexity and large number of variants that comes with it, mean that your current CAE processes and systems are unable to cope with the demands placed on them.
- The wide range of CAE tools from different disciplines, such as 1-D, MKS, CFD, FEM, etc., make data exchange more difficult.
- The effort involved in procuring and preparing the data linked to simulations and ensuring the quality of the results (auditability) is putting an increasing strain on your processes and overburdening your resources.
What if…
… you no longer had to store and version your simulation data in the file system and a comprehensive, interdisciplinary SDM system could take over management of data flows and process chains instead and dramatically boost their efficiency?
… the time and effort required for activities with low added value (e.g. data acquisition and preparation) could be minimized through automation, thus allowing you to concentrate on your value-added?
… the systems engineering data that is linked to simulations could be managed in a reliable manner on the basis of maturity level?
… your process documentation and documentation of deliverables were transparent, enabling you to fulfill the requirements from audits without any extra effort?
… you could carry out a significantly greater number of calculation projects with calculation variants using the same number of staff?
Further highlights:
- Sensitization/introduction of SDM, assessment of its benefits and selection of appropriate SDM systems using a proven procedure model from :em AG
- Implementation of concept and feasibility studies including process and use case analyses, IT interface analysis and IT infrastructure planning, strategic evaluation and cost/benefit analysis, creation of reference processes, method development, recommendations for action and project planning.
- Due consideration of adjacent process chains such as test data management and product data management (design), BOMs, change management, material databases, ERP systems, order management, etc.
- Creation of technical system specifications for documenting requirements relating to CAE and/or SDM systems, including development of the technical data model.
- Creation of interface software, system integration, customization of SDM solutions, technical and user support, testing and acceptance of the specified solutions.
- Agile implementation and rollout using Scrum methodology at the interface between user and system provider, e.g. in the role of scrum master.
