Recently, Kansei (emotion) engineering has attracted interest in artifact design since it helps ensure customer-defined satisfaction in the current scenario of global competition and short product life cycles. Accordingly, intelligent decision-making through multiobjective optimization has been proposed as an efficient method for human-centered manufacturing. From this viewpoint, in this study, we apply a multiobjective optimization method referred to as MOON2R to an ill-posed problem that involves both qualitative and quantitative performance measures. Additionally, to facilitate the portability of the proposed method, especially in multidisciplinary decision-making environments, we implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the method through a case study.