Automotive Upright Lightweighting and Multi-Process Cost Analysis
In the race to reduce unsprung mass and maximize EV range, every gram counts. But traditional CAD workflows force engineers into an impossible choice: spend weeks iterating on topology optimization across multiple manufacturing processes, or settle for the first feasible design and leave performance on the table.
This case study documents how a high performance automotive team used Cognitive Design to break that compromise. Starting with a legacy steel upright that was clearly over engineered but difficult to improve with conventional tools, we generated and evaluated 100+ design variations across three distinct manufacturing pathways (additive manufacturing, CNC machining, and die casting) in a single integrated workflow.
The result: 30% mass reduction on the production design, engineering lead time collapsed from 96 hours to 4 hours, and a complete cost-performance trade-off matrix across all three manufacturing processes — delivered before a single physical prototype was built.
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In a documented EV upright lightweighting case, Cognitive Design generated and evaluated over 100 design variations across three manufacturing pathways (additive manufacturing, CNC machining, and die casting) within a single integrated workflow. All variations were evaluated simultaneously against structural performance, cost, and manufacturability, replacing a sequential design-simulate-select cycle.
Cognitive Design compressed upright design exploration and validation from 96 hours with conventional software to just 4 hours, a 96% reduction in engineering lead time. This enables rapid evaluation of over 100 manufacturing-ready variations within a single working session, compared to 2-3 conservative concepts typically explored using traditional CAD/FEA workflows.
The optimized Ti-6Al-4V upright achieved a 30% mass reduction, dropping from 3.20 kg to 2.24 kg, while maintaining structural integrity under critical braking and cornering load cases. For EV applications, reduced unsprung mass directly improves range, handling response, and ride quality across the vehicle platform.
By eliminating traditional tooling requirements for additive manufacturing routes, Cognitive Design reduced production lead time from 8 weeks for cast parts to 5 days for AM-printed components. This acceleration is critical for prototype validation phases, where rapid iteration between design and physical testing is a key competitive differentiator in automotive development programs.
Cognitive Design's Design Explorer automatically calculates and compares unit cost across all manufacturing routes explored within a study, incorporating material cost, machining time, tooling amortization, and production volume inputs. This allows engineering teams to make data-driven manufacturing route decisions at the concept stage, rather than discovering cost implications late in the program.
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