The winner in the Full Vehicle category was General Motors’ 2019 Chevrolet Silverado, which weighed in at an impressive 450 pounds (204.5 kilograms) lighter than its predecessor. BMW Group claimed the Module category with the first 3D printed metal component used in a production series vehicle, which captured a 44 per cent component weight savings on the 2018 BMW i8 Roadster.
Asahi Kasei Corporation’s Super Lightweight Pedal Bracket for the Mazda MX-5, Sika Automotive’s Ultra Lightweight Constrained Layer Material System, and United States Steel Corporation’s Martensitic Advanced High Strength Steel, Mart-Ten 1500 took the top honours in the Enabling Technology category. The award for the new Future of Lightweighting category, chosen by MBS attendees, went to American Axle & Manufacturing, (AAM) for its Quantum Driveline Architecture program.
‘It was impressive to see the high quality of this year’s Altair Enlighten Award applications. Nominations from OEMs, suppliers, materials technology companies, start-ups and academia demonstrate the tremendous and varied weight reduction effort being achieved across the global automotive industry,’ said judging chair Carla Bailo, President and CEO of CAR. ‘We were also thrilled at the response to the new Future of Lightweighting category introduced this year, which highlighted some highly innovative solutions holding great promise to advance fuel efficiency and automotive sustainability.’
‘Our judging panel had a very difficult task selecting this year’s award winners among so many high quality entries,’ said Richard Yen, Senior Vice President of Global Automotive and Industry Verticals at Altair. ‘I would like to personally congratulate our award winners and thank all of our finalists and applicants for participating. It’s a rewarding experience each year to witness how simulation-driven design strategies, new materials and advanced manufacturing processes are advancing automotive lightweighting by offering new opportunities to innovate weight efficient products from the start.’