Designing for Six-Sigma Quality with Robust Optimization Using CAE 2002-01-2017
Although great advances have been made over the last two decades in the automotive structural design process, tradition and experience guide many design choices even today. The need for innovative tools is stronger now more than ever before as the design engineer is confronted with more complex, often contradictory design requirements such as cost, weight, performance, safety, time to market, life cycle, aesthetics, environmental impact, changes in the industry's business models, etc.
The ever-increasing use of optimization tools in engineering design generates solutions that are very close to the limits of the design constraints, hardly allowing for tolerances to compensate for uncontrollable factors such as manufacturing imperfections. Optimum designs developed without consideration of uncertainty can lead to non-robust designs. Reliability-Based Design Optimization (RBDO) methodologies not only provide improved designs but also a confidence range for simulation-based optimum designs.
In this research effort, a six-sigma robust design formulation is presented along with an example that demonstrates the advantage of robust versus deterministic optimization.