Reliability-based robust design optimization: A general methodology using genetic algorithm

• A general methodology for designing robust and reliable products is proposed.
• A genetic algorithm is used to solve the optimization problems.
• A good agreement between design and manufacturing stages is provided.
• More than one quality characteristic is considered.
• The correlation structure between quality characteristics is considered.

In this paper, we present an improved general methodology including four stages to design robust and reliable products under uncertainties. First, as the formulation stage, we consider reliability and robustness simultaneously to propose the new formulation of reliability-based robust design optimization (RBRDO) problems. In order to generate reliable and robust Pareto-optimal solutions, the combination of genetic algorithm with reliability assessment loop based on the performance measure approach is applied as the second stage. Next, we develop two criteria to select a solution from obtained Pareto-optimal set to achieve the best possible implementation. Finally, the result verification is performed with Monte Carlo Simulations and also the quality improvement during manufacturing process is considered by identifying and controlling the critical variables. The effectiveness and applicability of this new proposed methodology is demonstrated through a case study.