Today’s world operates at a furious pace. Modern technology, including landscape-altering technology like generative artificial intelligence (genAI), is reshaping how products are designed, made, used, and discarded. In industries from automotive and aerospace to electronics, life sciences and beyond, research, development, and manufacturing design cycles continue to condense. This presents product engineers and designers with a variety of hurdles, and one big, overarching question in all their projects: How can we continue to accelerate design cycles to meet market demand without compromising products’ performance or quality?
The answer is AI-powered engineering. Organizations that opt not to use AI-powered engineering workflows are placing themselves at a serious disadvantage in a global marketplace that’s increasingly driven by the widespread use of AI. Though AI use in engineering and beyond isn’t free from uncertainty and risk – no technology is – it’s clear that the proverbial Pandora’s box that is AI won’t be closing anytime soon.
On the other hand, organizations that have begun implementing AI-powered engineering workflows are discovering that it’s driving innovation at unprecedented levels. How? Let’s dive in and find out.
MOVING BEYOND MERE SIMULATION
Simulation capabilities are a must-have in the modern engineering landscape. But AI-powered engineering isn’t defined by simulation alone. True AI-powered engineering workflows combine simulation with enterprise-level data analytics and high-performance computing (HPC) capabilities to catapult the design process beyond “what-if” scenarios to create new, unique, data streams. In other words, AI-powered engineering goes beyond simulation and adds data analytics and HPC to augment the best of simulation’s abilities. This combination unlocks brand-new possibilities and allows designers and domain experts to get more from their workflows.
In addition, AI-powered engineering approaches allow designers to consider multiple objectives simultaneously throughout the design life cycle. That means that beyond costs and strength, for example, designers and engineers can also use these workflows to optimize aesthetics, comfort, and manufacturability, the latter being pivotal in the modern design life cycle.
INNOVATING FASTER THAN EVER
Time is everything in modern design and engineering. Delays and lengthy iteration trials are a surefire way to damage morale and miss out on the market’s biggest opportunities. AI-powered engineering streamlines the engineering life cycle by taking a fraction of the time needed for traditional solver simulation while simultaneously enabling engineering teams to test more design variations.
Moreover, AI-powered technology allows teams to leverage historical data to deliver the best physics predictions possible. This is a massive capability; before AI, think of how much knowledge was lost in the testing life cycle among different steps, products, and teams. Now, AI can unlock that previously untapped value. The market’s best tools ensure reliable predictions by assessing and validating predictions against traditional solver simulations. In all, AI-powered engineering workflows, driven by market-leading technology, can deliver predictions that are up to 1,000x faster than traditional solvers, enabling teams to evaluate more concepts and make better design decisions.
OPENING NEW AVENUES
Implementing AI-powered engineering workflows not only moves beyond simulation and allows your team to innovate faster, it also opens new design paradigms. Above all, digital twin technology stands out for its ability to give teams unparalleled insight into their designs. Put simply, digital twin technology empowers organizations to transform their products, systems, and processes for a new era of engineering.
With digital twins, teams can rely less on physical prototypes, which can be time- and resource-intensive. Because digital twin combines leading simulation, HPC, AI, and data analytics capabilities, teams can design, build, test, optimize, evaluate what-if scenarios, perform predictive maintenance, and extend the remaining useful life (RUL) of their products without using physical prototypes. They can also enable comprehensive cross-functional system evaluation, which eliminates information silos and communication bottlenecks during product development. With all this, organizations become more efficient and can deploy digital twin technology when and where they need it from concept design to in-service performance. This is a game changer for organizations of any size in any industry, saving them time and money while improving their products at never-before-seen speeds.
WRAPPING UP
AI-powered engineering is a breakthrough in the world of engineering and design for many reasons, but it all boils down to a key value proposition: doing more with less. Essentially, AI-powered engineering workflows are so powerful because they’re essentially giving engineers and designers a head start in any design they create—and then giving them the resources to test more variations much faster than with traditional solver simulation. In short, AI-powered engineering lets you recycle your organization’s past experiences and expertise to design better products faster. This is something only the convergence of simulation, data, and HPC can bring to the fore.
In a world where the pace of competition is only getting fiercer and faster, AI-powered engineering can help you stay ahead of the market and deliver unmatched value—no matter what you’re designing.
To learn more about Altair, visit https://altair.com/. To learn more about Altair’s AI-powered engineering capabilities, visit https://altair.com/ai-powered-design.