Designing Better Products Faster

Whether your company is beating the competition to a new market or responding to customer demand, seizing the window of opportunity when customers are most receptive to your product is critical.

Releasing a product at the right time requires engineering and process efficiency—from first concept through final manufacturing. The old practice of developing a design, building a physical prototype, testing, redesigning and then building a new prototype is no longer sustainable. This is especially true as products become more complex, using mechanical, electrical and embedded software subsystems. Not only are physical mockups expensive, testing them tends to find isolated problems rather than address systemic design issues.

Engineering simulation and virtual prototyping have reduced reliance on physical testing and pushed verification activities to earlier in the design. Engineers using these tools assess designs more comprehensively and at a fraction of the time and cost. Simulation will never fully replace physical testing, but it can reduce the number of physical prototypes and testing cycles that are necessary, shaving months off development lead times.

The demand for shorter time to market, however, is relentless. In the automotive industry, average lead times have been reduced from over four years to two and a half years. Yet the industry is pushing to drive this below two years, despite the dramatic increase in product complexity. This trend holds true for almost every industry. Simply applying simulation to verify design and reduce physical testing is not sufficient; simulation has to be applied efficiently throughout the design cycle.

Process compression centers around three main strategies:

1. compressing each design cycle,

2. reducing the number of cycles and

3. parallel—or concurrent—engineering.

At most companies, engineers, designers and analysts spend considerable time performing routine, repetitive tasks and procedures. Often, these procedures differ between teams, are undocumented, or are inconsistent. One way to compress each design cycle is to create custom, repeatable simulation workflows so teams can focus on results and make the best decisions earlier.

High-performance computing (HPC) is paramount for faster design cycles. The growing complexity and size of simulations can bring a well-equipped desktop computer to its knees for hours or even days. HPC enables engineers to create large, high-fidelity models that yield accurate and detailed insight into the performance of a design. Not only can engineers solve larger models faster, but they can also perform more simulations using different design parameters to explore a larger design space.

Consolidation is Key

Compressing the time spent on each cycle is important, but you can attain even greater results by reducing design iterations. An enterprise platform for executing and managing a broad set of simulation applications and performing multi-objective optimization are key to finding the best design, faster. For example, an automotive supplier might need to maximize the heat transfer coefficient of its disk brakes while at the same time meeting braking performance, durability and noise requirements. Finding the design that satisfies all of the requirements involves a variety of engineering disciplines and simulating different physics. Many companies today address this situation by using siloed design teams that deploy multiple tools from separate vendors. This approach is hardly efficient; the Aberdeen Research Group found that reconciling data formats over multiple platforms alone costs companies an average of 3.6 hours per analysis, with some companies reporting a loss of eight hours—an entire workday—per project. With a consolidated simulation platform, designers can effectively execute efficient multiphysics simulations that enable them to make design decisions earlier. Not only do these platforms support multi-objective optimization, but they make it possible to analyze and evaluate trade-offs in complex architectures, requiring fewer iterations per cycle.

And to parallelize design activities, model-based system engineering (MBSE) tools are being adopted to better manage and communicate the complexities of today’s product architectures. MBSE principles use living, executable models, rather than static CAD models, documents or spreadsheets as the source of truth for product design. These models provide a thorough understanding of the dependencies, data and interfaces between subsystems so that engineering teams break linear, waterfall development processes and adopt concurrent engineering practices.

By adopting process compression best practices, you can respond to constantly changing market conditions faster and more precisely while designing better, more innovative products for your customers.

Todd McDevitt is director, Corporate Marketing, at ANSYS. Contact him about this commentary via [email protected].