Combining Iterative Heuristic Optimization and Uncertainty Analysis methods for Robust Parameter Design

† School of Engineering, Universidad de los Andes, San Carlos de Apoquindo 2200, Santiago, Chile ‡ Computer Science Department, School of Engineering, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Santiago, Chile In the last years, several works have pointed out that products and processes lack quality because of performance inconsistency, often produced by parameters that are uncontrollable in the manufacturing process or the product usage. Robust design methods are aimed at finding product/process designs that are less sensitive to parameter variations. Robust design of computer simulations requires a high number of runs, making it prohibitive for timeconsuming simulations. This work presents a novel methodology for robust design, which integrates an iterative heuristic optimization method with uncertainty analysis to achieve effective variability reductions, exploring a large parameter domain with an accessible number of simulations. To prove the effectiveness of this methodology, the robust design of a 0.15μm CMOS device is shown.