QFD method is a tool for improving the quality of production and services. The existing input data for QFD such as the weight of customer requirements, the weight of the relationship between customer requirements and engineering characteristics, and also the weight of the relationship between engineering characteristics are often limited, not exact, or in the best state ambiguous, which leads to uncertainty in the results. The impression of input data uncertainty is apparent in QFD output which causes variability of the analysis results of QFD. Being fuzzy is a characteristic that leads to uncertainty in input data in consequently changes in output results. Therefore, a few studies have been conducted on evaluating the changeability of the obtained results from QFD by the title of “Robust QFD”. In the present study, we introduce a framework for Robust QFD, which evaluates the power of QFD based on having the exact output data, under the condition of uncertainty resulting from having fuzzy inputs. In order to evaluate and study the desirability of the presented framework, the proposed methodology is demonstrated on a numeral example and an index for Robustness has been introduced. The findings indicate that the proposed methodology helps to a more certain resulting from QFD.
