To achieve competitive design, it is essential to develop an optimization method that ensures both high customer satisfaction and robustness for products with multiple criteria. While several studies have proposed optimization methods that integrate TOPSIS with Taguchi method or desirability function, no single study has yet combined all three methods into a unified optimization framework. Therefore, this study proposes an integrated optimization method that combines TOPSIS, Taguchi method and desirability function. The overall process of proposed method is based on the TOPSIS framework. To incorporate Taguchi method and desirability function into TOPSIS, we propose using desirability function for normalization, replacing the traditional vector normalization used in standard TOPSIS. In addition, Signal-to-Noise(S/N) ratios are calculated to evaluate the degree of customer satisfaction. To demonstrate the effectiveness of the proposed method, a hypothetical example is generated under specific conditions, and the resulting rankings are compared with those derived using the original TOPSIS approach. The comparison revealed that the rankings of design alternatives differed between the original TOPSIS and the proposed method. This difference is attributed to the influence of the desirability function’s threshold points, the specific type of desirability function applied (from Kano’s perspective), and the Taguchi S/N ratio used to assess satisfaction levels. These factors enabled a more nuanced evaluation of customer satisfaction and robustness, thereby validating the effectiveness of the proposed optimization method.

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation( max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

  According to the automated manufacturing processes followed by the development of computer manufacturing technologies, products or quality characteristics produced on the processes have measured and recorded automatically. Much amount of data daily prod

저등급 석탄인 갈탄(lignite)을 순환 유동층 가스화기(circulating fluidized bed gasifier)의 효과적인 가스화를 위한 공급탄으로 제조하기 위하여 모든 조건들은 동일하고 스크린의 크기만을 변경하여 목적하는 입도분포 특성을 달성하는 최적조건을 찾기 위한 실험을 수행하였다. 가스화기 공급탄은 0.045~1 mm 크기로 85 wt% 이상이 요구되며 이러한 입도분포를 갖는 공급탄을 제조하기 위해서는 경제적이면서도 효과적인 공정 설계가 반드시 필요하다. 따라서 본 연구는 중국산 갈탄을 해머밀로 효과적으로 분쇄하기 위하여 다구치 설계를 사용하였으며, 설계조건에 따른 실험결과 및 통계분석 결과 95% 유의수준에서 1차 스크린의 크기는 3 mm, 2차 스크린의 크기는 1.3 mm인 경우가 최적화된 조건인 것으로 나타났다.