The Changing Role of Computational Simulation throughout the Product Lifecycle


Computational Simulation has traditional been used to replace physical testing. Later it evolved to being a design tool. And simulation is also very relevant in studying manufacturability and manufacturing processes. Different degrees of fidelity models are used depending on the need for accuracy or speed. Combined with optimization technologies looking at design requirements vs. a manually driven virtual testing loop, simulation has made a big impact improving products and lowering cost.


The latest evolution has seen the spread of computational mechanics into the realm of operation. The Internet of Things requires a Digital Twin to simulate a product or system while it operates to include operational data and make decisions about maintenance and operability. Further the digital twin has use in close loop engineering where operational data makes it into design decisions.


Now design and decision-marking throughout the product lifecycle are governed by applying computational simulation, machine learning, and optimization. This leads to new requirements on multi-physics simulation, virtual test setups, and design environments. Each phase has different requirements on fidelity of models, may it be model-based or data-based simulation.


The note will discuss the contributions of computational mechanics to managing the product lifecycle. Relevant methods and innovations as well as the needs for new technologies will be highlighted. Commercial software developers are technology providers that utilize academic research and industrial advances to improve and rationalize design, validation and verification as well as operation of products and product systems.