DE · Topics · Resources · Design Exploration and Optimization · Sponsored Content

Case Study: 3D Modeling for Faster Engineering Results

Developers at SLM Solutions AG replaced their conventional CAD system with a more user-friendly solution for faster design exploration using ANSYS Discovery SpaceClaim.

March 25, 2019

SLM Solutions AG manufactures three types of selective laser melting (SLM) machines and metal powder for its clients’ 3D printing needs.

The company serves a wide variety of industries, specifically aviation and aeronautics, automotive, energy, toolmaking and medical and dental. Clients use SLM products to produce prototypes and small series rapidly and cost-effectively without the need for tools or molds.

Challenges

Like its clients, the company also faces the challenges of visualizing and testing ideas more rapidly. And, as a machine builder, they are often pressed to develop parts for machinery ASAP. To overcome these challenges, company developers wanted to replace their conventional CAD system with a more user-friendly solution for faster design exploration.

Download Case Study: 3D Modeling for Faster Engineering Results

Latest News

Massivit 3000 Large-Format 3D Printer Launches
The new printer enables high-speed production of 3D window displays, 2D/3D combined point-of-purchase displays, interactive event props, and molds...

Indy Autonomous Challenge to Returns to Indianapolis Speedway
Race set to feature a head-to-head race of possibly the fastest autonomous racecars piloted by artificial intelligence driver software, organizers...

Desktop Metal Releases Binder Jet 3D Printing Upgrade
The Production System P-1 metal binder jet 3D printer will be offered with a Reactive Safety Kit for high-speed production...

MathWorks Advances Software-Defined Workflows with NVIDIA’s Help
Developers can use their existing MATLAB Algorithm Codebase to develop and deploy AI-enabled applications via the NVIDIA Holoscan platform.

AI in Design: In Need of New Hardware
New hardware options are emerging to support artificial intelligence use cases.

Can AI Eat Itself?
Looks like synthetic training data is here to stay—it's something engineering organizations should keep a close eye on.

All posts