Stanley Black & Decker (SBD) is a diversified global provider of hand tools, power tools
and related accessories, mechanical access and electronic security solutions, healthcare
solutions, engineered fastening systems, and more. The company delivers the hardworking,
innovative, powerful tools that help professionals around the world build, repair, and
protect the world’s most valuable things.
SBD is the leader in tools and security with brands including Stanley Tools, DEWALT,
Mac Tools, Porter-Cable, and more. Its products range from airport doors to residential
locks and deadbolts to the hydraulic breakers that rescue trapped earthquake survivors.
According to the company, "No matter where you live, what car you drive, what stores
you shop at, or what building you work in, you can bet that we had a hand in making it
work. And you can guarantee that we’ll keep making it work."
The Challenge: Improving the Capacity for Design Optimization
As a global power tool leader, SBD is constantly seeking ways to maintain a competitive
edge and bring better-performing products to market faster. In particular, when it came
to optimizing the hammer mechanism design for their top-selling rotary hammers,
SBD engineers knew they needed a computer-aided engineering (CAE)-based approach.
“The hammer business is extremely competitive, and rotary hammers are the most
complex power tools on the market, so we have to use the most innovative methods
available to optimize performance,” says Andreas Syma, director of global CAE at SBD.
“Optimization by CAE is the only realistic way to achieve this; the requirements are just
too complex to rely on experience based knowledge or pure physical testing.”
CAE-based optimization enables engineers to:
- Handle the extremely high complexity of a physical product
- Test several hundred designs at a time
- Provide a deeper understanding of how the product physics works
“Real optimization is only possible with computer-aided methods,” explains Syma.
“There is only so far you can take a system with physical testing — you have to explore
how the physics works at a higher level, made possible with CAE, to gain new insights and
see what is needed to improve the system. The simulation-based optimization approach
gives a very high reward on engineering work, in terms of performance, durability, cost
and weight — it results in a much higher-value product, especially when applied early
in the process.”
Previously SBD had been using workstations running LS-DYNA with an optimization runtime
of about three weeks. “A three-week runtime wasn’t sufficient to stay competitive — our goal
was a runtime of one weekend, where our engineers could start a job Friday and have the
results Monday,” said Syma.
SBD team members knew they needed more computational power to drive desired
performance improvements, but they were concerned about simply investing in more
hardware or compute cores for three reasons:
- Cost of high-performance computing (HPC) hardware/cores
- Effort to maintain and support a complex HPC system
- Ability to fully leverage this hardware with the necessary software licenses to keep