Modeling, Simulation, Optimization and New Materials for engineering
Better and faster engineering with powerful simulation
Purpose of advanced simulation modelling
The measure of progress has always centered around how we can achieve better results and how we can do that more quickly. The modern moon shot is the sprint to develop a vaccine or achieving a truly circular economy. These efforts demand new heights of quality and speed in engineering – that is the purpose of our field of innovation Modeling, Simulation, Optimization and New Materials at Bosch. It’s our goal to bring products faster to market, save costs and find new materials to use.
On a mission
We are dedicated to creating a digital holistic product life cycle design that will bring innovative products first to market. To achieve our mission, we pursue several key objectives. We are creating models for holistic digital twins in the value chain – from cradle to grave. We leverage multiscale technology – from the nanoscale to component and system levels. We speed up computation using AI and quantum computing. We enable automated and robust design practices through optimization and uncertainty quantification. And, we aim for virtual release and validation of components.
Research towards virtual product engineering
Currently, considerable time and costs are required to develop components, processes and systems. A lot of experience is needed to support these efforts and the numerical models are grounded in experimental tests. The experimental approach often yields suboptimal solutions, though. Main design parameters such as process parameters in manufacturing cannot be captured with sufficient accuracy. Additionally, it is impossible to experimentally analyze a constantly growing parameter field in more complex systems within a highly dynamic market environment. Ready-to-use tools and methods that transfer to new engineering tasks without great effort are the key to accelerating the pace of virtual product engineering.
The right solutions require combining methods from our field of innovation with other technologies over many scales. The challenges to overcome can be categorized under three thematic areas: mastering complexity, AI and virtualization, and computational speed.
Overcoming these challenges can enable engineers to develop more robust solutions or discover new capabilities, which couldn’t easily be found with existing, slow trial-and-error methods. The time for a product engineering process could be reduced by 30–50% when the engineering goals can be more specific from the outset. Even modeling could be created more quickly and with less experimental input while producing better predictions.
Ready-to-use tools and methods that transfer to new engineering tasks without great effort are the key to accelerating the pace of virtual product engineering.
Meeting the challenges
Bosch Research has answers for each of the three important challenge areas that have to be addressed to make advanced virtual product design a reality. To master complexity, we favor a multiscale modelling approach. This approach makes the simulation based on physical and chemical mechanics to the greatest extent possible. It is applied from the smallest scale of atoms through components to the entire system. The result is a reduction in parameters, which in turn boosts the exactness of the simulation modelling. There are limits to this approach. It could be, for example, that an understanding of certain physical or chemical mechanics is limited or missing. Enter AI.
A capable and effective AI is a major challenge area for the future we envision. Combining a data-based AI with the expert scientific knowledge gives way to hybrid modelling. Hybrid modelling is an important tool that enhances the effectiveness of current modeling methods, and it is a fundamental piece in achieving our aims for virtual product design. There is a lot of work to structure existing data as well, for example using text mining.
All of this work creates a demand for extreme computational speed – the third major challenge area. Achieving next-level computational speeds requires a bundle of measures. AI will play a significant role. Also, it will be critical to develop better and faster algorithms for computational speed. An exciting front in this challenge is the onset of quantum computing. Bosch is working with companies specializing in this technology as well as on publicly funded research projects. Quantum computing will achieve major advances in processing speed, reducing the time for computation and offering better generalization abilities – all key objectives of our mission.
Modeling, Simulation, Optimization and New Materials is a field of innovation at Bosch that advances various technological fronts in pursuit of advanced virtual product engineering. We strive to save costs, identify new materials and discover new business models using digital holistic product life cycle design.