Model Driven Design

Even though the introduction of 3D modeling software in the late 1960s brought engineering one step closer to the model-based approach, downstream processes have continued to rely heavily on information carried by traditional drawings.  

Engineering departments today must develop smart products that integrate mechanical functions with electrics, electronics, and controls, utilize new materials and manufacturing methods, and deliver new designs within ever shorter design cycles. This requires current engineering practices to evolve into a Digital Twin approach, which enables to follow a more predictive process for systems driven product development.

In short, a model is a representation of something that can be realized in the real world, and a model is intended to help us understand the real-world object, system, or phenomenon. A model can represent a small entity or an extensive system of systems. The more accurate a model is the more value you get from using it.

Requirements Engineering

One of the cornerstones of model-based engineering is understanding customer and business needs, breaking them down to product performance requirements, and allocating the requirements to downstream functions for realization, verification, and validation.

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Product Performance Engineering

Another cornerstone of model-based engineering is defining product behavior and balancing potentially conflicting performance from the early development stages until the final performance validation and controls calibration. To deal with an increased number of requirements, use cases, and architectural variants, you can rapidly create heterogeneous system simulation architectures and share your models with the global engineering team. In addition, to help you bring more successful products to the market rapidly, the concept of a digital twin has been extended to on-board software engineering.

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Electromechanical Engineering & Simulation

Engineering drawings have been around for thousands of years, and downstream processes continue to rely heavily on information carried by drawings. Digital transformation has however changed the status quo. Digital Twins have become a crucial vehicle for communicating design intent, simply because models make systems and their behavior easier to understand and simulate. Beginning with understanding what a product or part is like. State-of-the-art engineering applications with virtual reality support allow for a life-like experience of seeing 3D parts and assemblies. Making it far easier to understand what they are like and what it is like to interact with them than interpreting 2D views. Computer interpretable models, which together can represent all aspects of real-world systems with the desired level of accuracy further improve the capability to understand how a given system will behave under different circumstances.

3D simulations can be used to predict the performance of your designs with a wide range of CAE methods including finite element, boundary element, computational fluid dynamics, and multi-body dynamics. And by linking behavior models with 3D models, you can achieve unmatched accuracy of predictions. Combine 3D design and simulation tools with design optimization tools unleashes the power of technology to develop revolutionary products quicker than you could ever imagine.

Verification and Validation Closes the Loop

Use Teamcenter® collaboration platform to assign product performance requirements in a closed-loop process, where requirements are tied to the test cases that validate them against a design based on those requirements. Test cases can be either virtual, i.e. simulations, or tests on physical prototypes. Verification requests carry all required input for setting up the simulations or tests, as well as the outcome of requirements verification.

As a result, you get full visibility into the requirements verification and validation process, along with the status of current V&V efforts, and any issues generated during testing. Test results in turn feed issue resolution and change management processes to manage compliance issues (as well as maintain evidence of compliance for auditing purposes). This sets up an organization for significant V&V productivity improvements.

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