- Engineering Workflow Automation
- Design Space Exploration
Meeting up with leading manufacturers at last year’s Optimus World Conference provided great opportunity to learn about their latest process integration and design optimization (PIDO) achievements. They clearly expressed that more Optimus PIDO technology advancements will play a critical role in meeting the development challenges they see ahead of them.
At the conference we spent valuable time talking with representatives from various customers, including Thales Alenia Space, Toyota Motor Corporation, Volkswagen, Safran, Philips Consumer Lifestyle, Great Wall Motor Company, l’Orange and Saint-Gobain. In our discussions it became apparent that they all share a PIDO vision that takes simulation based engineering processes to the next level – truly allowing them to “optimize from well to wheel”.
So let us share with you a brief synthesis of the most common requirements they see to help them cope with future development challenges:
Tackling real-world optimization challenges typically involves improving multiple design objectives. A Volkswagen representative, for example, told us explicitly that car design optimization is never just about lowering weight, but always linked to a range of performance attributes. Minimizing weight should not compromise other performance measures, or performance should be further improved with the same weight.
In many engineering projects, PIDO technologies must drive simulations successfully to find an efficient balance between contradicting objectives. Manufacturers therefore benefit from executing multi-objective design optimization in a fast and interactive way, such that they can easily follow up and influence the balancing strategy.
The applications presented at the Optimus world conference prove that industrial-scale optimization projects can be executed without violating any design constraints. And, let’s be honest, that’s a big step forward compared to earlier days when simulation based design was approached in an iterative way. In this manual and iterative process, even the brightest engineers could easily violate some design constraint sooner or later.
Having realized the benefits of dealing with design constraints as part of PIDO, manufacturers are already looking toward solutions that help them manage constraints throughout the entire process rather than just not violating any design constraints. They could highly benefit from an interactive dashboard that monitors the status of each individual constraint that arises from market and manufacturing driven requirements.
This would help them to develop a clear view on the so-called feasible design space, while informing them on the robustness of individual design solutions at the same time. The result of all that? It just becomes so much easier to have a holistic view on the design space and to make informed decisions during the entire process.
Once too often, engineering teams get buried under the massive amounts of data generated through simulation and physical testing. As a result they spend a lot of time and effort to retain the information that matters most. All manufacturers we talked with therefore look for solutions offering intuitive data mining capabilities, allowing them to acquire even more engineering insights than possible today.
Highly interactive data and result displays in particular would make it easy for them to interpret all available information, to evaluate results through different stages of the development process and to really learn the lessons on which to base critical engineering decisions. Now that would empower their experience!
Both simulation and optimization methods have evolved over time such that more simulations can be used as part of the design optimization process – even when that process has to fit within a shorter time window. And yet - with the next challenge always already in sight, manufacturers are constantly looking for further time gains that help them improve the overall efficiency on any optimization project.
Obviously, more performing algorithms can significantly contribute to that objective. But even more important may be the ability to customize and fully automate optimization projects – from setting up the simulation workflow to building high-quality surrogate models. Even today – with Optimus’ powerful UCI/UCA capabilities – there’s already a good toolset to make that happen.
Today there exist a multitude of optimization methods, each with their specific strengths and weaknesses. Mechanisms are already in place to automatically select the most suitable method and execute it in the most efficient way, based on the nature of the problem at hand and the time that is available.
Manufacturers find this a great improvement, but want solutions to become even more robust so that users need to enter a minimum of information to get the process started. They are also looking into the potential of automatically switching between methods during the design optimization process itself, to use all methods at their full strength during every stage of the optimization process.
The above summarizes the needs that many of our Optimus customers have identified as important to further help them excel in engineering benchmark products. So here we arrive at the really good news. With our own new PIDO capabilities to be released soon, Noesis Solutions will again make the life of engineers a lot easier and more effective. Those new capabilities will further free their hands to focus on learning the design space and to make informed engineering decisions in search of the most feasible product design.
Want to know more about all this? Then you should definitely watch out for our next blog posts, each one dedicated to a specific need introduced in this post. We will further elaborate on the challenge at hand and give you a sneak preview on how our new Optimus capabilities will successfully respond to it.
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