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What if your product development team had a genie in a bottle that could pop out and immediately optimize virtual prototypes every time the team tried something new?
No highly trained optimization specialists. No time-consuming automation scripts to write. No complex analysis of multiple parameters.
SNAP! Here’s your optimized prototype data.
The product-development process would be faster, easier and more effective, and costs would drop. The potentially bigger gain, though, would be wider adoption of design space exploration (DSE) by essentially flipping the simulation process so it is less about meeting requirements and more about building knowledge, impressing customers and breaking new ground.
With more time and resources to push boundaries, design teams could use simulation to find new ways to solve existing challenges, as well as envision new products that previously would have gone undiscovered.
"DSE will spawn new thinking about what product development teams contribute to new revenue sources, cost improvements, and ongoing innovation "
Easier, faster and more affordable design optimization
What many people don’t know is that the “genie in a bottle” exists and is better known as intelligent automation: that is, software-driven processing that can quickly integrate and assess disparate data sets, and then make decisions and perform tasks that humans alone need hours or days to accomplish.
It’s a new type of software capability becoming more commonplace across businesses. In the finance function, for example, intelligent automation is shrinking how long the monthly “closing of the books” takes from days or weeks to minutes. It’s also the power behind generative design For digital product or system simulations, intelligent automation can:
• Integrate data from any and all simulation programs in use
• Perform computational analysis to optimize the model in minutes
• Feed the optimized model data back into the simulation programs in use
Moving from design optimization specialists to intelligent software
DSE isn’t new, but an intelligent DSE capability is. Because DSE is time-consuming, its use has been limited to simulations where miniscule tweaks can have a substantial impact on performance—and return on investment for both the company and its customer. Think Formula One race cars, where eking out the last few percentage points of power mean the difference between winning and losing; or aerospace engines, where slightly more efficient jets save on fuel costs and reduce environmental impact.
DSE is a process in which designers assume that the optimal design is unknown and initially uncharacterizable, and then they take steps to identify it. Traditionally it involves an iterative process in which teams of engineers from different disciplines, analysts and optimization specialists discover design conditions by designing, testing and analyzing a series of design options. Little by little, the parameters and possibilities are discovered, and then the final design is identified through a convergent design optimization algorithm.
The approach is sometimes confused with design optimization, which relies on upfront specification, with well-defined objective, design constraints and outcome preference. This approach essentially predefines the optimum solution, then employs an iterative, computational search to identify the final design.
Intelligent DSE gives every engineer the power of design optimization and design space exploration in a software application. The software capability comes as an out-of-the-box solution with drag-and-drop workflows that run in parallel with existing workflows. The engineer inputs the desired performance goals and the time available to optimize the design, runs the simulation model and design exploration, and the software outputs improved designs.
The value of intelligent software
While democratizing advanced design strategies is the primary value of intelligent DSE, forward-thinking companies will also use it to address some of the most common business challenges.
1. Increasing productivity. Running modern DSE software with intelligent automation as a parallel workflow to your existing processes makes both your specialists and existing technology faster and more efficient.
2. Offering customers new advantages. With intelligent DSE, you’ll be able to cost-effectively identify more ways to improve your products that give your customers a competitive edge. For example, a printing machinery manufacturer looking to design a more specialized (and thus higher margin) machine could use it to simulate how to improve upon printing speed, quality and reliability, so that they can identify a best trade-off design.
3. Replacing design skills and knowledge lost through retirements. Traditionally, engineers who wanted to integrate design tools to speed design optimization wrote their own software codes. Now manyof those specialists have retired or moved on, and they are not being replaced. Intelligent DSE automates the transfer of data, so engineering firms can focus on having good engineers rather than software developers; and, the resulting knowledge stays within the company.
4. Increasing margins on existing products. By using intelligent DSE to identify new materials or ways to use less material, manufacturers can reduce production costs while maintaining or increasing performance for the customer.
5. Innovating faster. Companies that rely on design and engineering innovation for their value proposition must continually strive to create better designs faster. Adopting innovative new tools and strategies, such as intelligent DSE, will help speed up innovation.
6. Designing entirely new products. Intelligent DSE allows product development teams to dedicate more time to solve more and different customer problems. It does the hard work of isolating the right data to quickly find the most promising solutions when none are known.
Additionally, intelligent DSE itself can be a design optimization strategy. For example, HEEDS, the DSE solution in the Siemens PLM product family, will determine which optimization method is best for a given project and then automatically run it. No one needs to be versed in the different methods, review the project requirements and then determine which methods to use and write a justification. The software does it all.
Carving out a profitable niche with DSE
Early adopters are reaping big gains. Becker Marine Systems uses intelligent DSE to identify and serve a profitable niche delivering customised energy-saving devices that make older ships more efficient. The Becker Mewis Duct, a simple piece of equipment, reduces fuel consumption by about 5 percent by enabling a vessel to travel faster at a given power level. The cost savings could be as much as $500,000—a result of using 2,000 tons less fuel.
For each duct, the design team draws on 40 design parameters to create a unique duct specified for each vessel’s hull. Working under strict timelines, the product’s success depends on rapid virtual prototyping using a DSE solution with intelligent automation.
Adding intelligence to mechatronic system design
At Airbus, engineers used intelligent DSE to improve the performance of the aircraft bleed-air system design on its A320 family of planes. The complex system feeds preconditioned air into multiple other systems that control cabin pressure and temperature, as well as wing de-icing and avionics. The Airbus team wanted to reduce pressure loss and improve temperature in the static-mixer design that comprises the bleed-air system.
In 2013, the design team had spent six months trying to optimize the system using the traditional DSE process. However, difficulties in integrating data across the design tools led to stability problems in the simulation and no solution was identified.
Four years later, armed with modern design tools, the team tried again, expanding its exploration to 11 parameters. Within two weeks, the team identified the optimum design to achieve the new temperature and pressure goals.
Intelligent DSE capability changes the game
Though it can seem magical, DSE software with intelligent automation capability is real and currently available. It’s a low-overhead, low-hassle investment that will dramatically speed up the product optimization process and improve outcomes by expanding simulation’s boundaries. It will spawn new thinking about what product development teams contribute to new revenue sources, cost improvements, and ongoing innovation.