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.

Today, as technology advances and market competition for products intensifies, the product design to improve customer satisfaction by accurately identifying customer needs is emerging as a very important issue for company. Accordingly, the customer-oriented or customer-centered design that maximizes customer satisfaction by grasping and analyzing customer requirements is in the spotlight as an important design theory. In this study, the customer-oriented design is defined as finding the optimal value of design variable with the maximum overall customer satisfaction while minimizing the difference in individual customer satisfaction responded to various customers from multiple product quality characteristics from the perspective of robust design. Therefore, this study presents a new method for modeling the customer preference structure as the different sets of desirability functions for multiple quality characteristics and proposes a new customer-oriented design approach by applying the desirability functions to Taguchi’s robust design process to deal with multi-characteristic design problem. Finally, the proposed method is illustrated with the Kansei engineering design problem of wine glass.

현대 사회가 복잡해지고 기술이 진보하면서 하나의 제품을 설계할 때 단일 특성이 아닌 다 특성을 갖는 제품을 설계하는 것이 요구되고 있다. 다 특성 설계 최적화 문제에서는 설계 변수의 최적값이 특성별로 다르게 되는 현상이 발생하고 이에 따라 하나의 특성에 대한 결과값이 좋아지면 다른 특성에 대한 결과값이 나빠지는 경우에 대해서 trade-off가 필요하다. 따라서 다 특성을 갖는 제품 설계 시 각각의 특성에 대한 성능을 최대화할 수 있는 효율적인 설계 방법의 필요성이 중요한 문제로 떠오르고 있다. 다 특성을 갖는 제품을 설계하는 연구는 오래전부터 중요한 문제로 인식되어 왔는데, 단일 특성에 대해 성능을 최대화하며 강건한 설계를 할 수 있는 다구치 기법과 다기준/다특성 의사 결정 방법인 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey relational analysis), PCA(Principle Component Analysis), Fuzzy Logic System을 통합한 연구들이 진행되어 왔다. 하지만 기존 연구들은 각각의 설계 대안들에 대해 다 특성 결과값에 대한 점수를 통합하여 종합 점수를 비교해 최적의 설계안을 도출할 뿐 설계자의 호감도에 대한 정보는 설계에 반영하지 못한다. 따라서 본 연구에서는 다구치 기법을 기반으로 각각의 특성들에 대한 설계자의 서로 다른 호감도를 함수로써 표현하여 강건성과 함께 설계자의 호감도를 동시에 설계에 반영할 수 있는 방법을 제안한다.

Today, as technology advances and market competition for products intensifies, the design to improve product satisfaction by accurately identifying customer requirements is emerging as a very important problem for company. Accordingly, Customer-Oriented Design, that maximizes customer satisfaction by grasping and analyzing customer requirements, is in the spotlight as an important design theory. In this study, Customer- Oriented Design is defined as finding the optimal value of the design variable with the maximum overall customer satisfaction while minimizing the difference in individual customer satisfaction responded to various customers from multiple product quality characteristics from the perspective of robust design. Therefore, in this work, we present a new method for generating a Desirability Function for each quality characteristic to deal with the multi characteristic parameter design with multiple quality characteristics. And we propose a new Customer-Oriented Design methodology that applies these Desirability Functions to Taguchi’s parameter design process.