Proposal of a new technique for prioritizing engineering characteristics in QFD

Abstract Quality Function Deployment (QFD) is a commonly used process for facilitating customer-oriented design of new products and services [1]. The initial module of QFD, known as the House of Quality (HoQ), aims to translate the customer requirements (CRs) of a new product/service into engineering characteristics (ECs), i.e., technical design features that directly impact the CRs. Fig. 1(a) exemplifies a portion of the HoQ in the form of a relationship matrix with CRs and ECs labelled in rows and columns, respectively; the symbols in Fig. 1(b) represent the intensities of the relationships between ECs and CRs. Additionally, each i-th CR is assigned a weight (w_CR_i) that reflects its importance from three complementary perspectives: the final customer, corporate brand image, and improvement goals for the new product/service in relation to existing counterparts in the market [1]. To prioritize ECs effectively, the QFD process necessitates considering their impact on the final customer. In fact, ECs that have relatively intense relationships with multiple CRs with relatively high w_CR_i values deserve more attention during the design phase. The conventional approach for prioritizing ECs is the so-called Independence Scoring Method (ISM), which calculates a weighted sum of coefficients (rij) derived from the numerical conversion of the relationship-matrix symbols (refer to Table 1(b)), utilizing the w_CR_i values as weights. The resulting weight of the j-th EC (w_EC_j) is determined by the following equation (an application example is shown in the lower part of Fig. 1(a)): w_EC_j=∑(∀i)(r_ij∙w_CR_i). (1) However, the ISM method incorporates two conceptually questionable operations: (i) a conventional and inherently arbitrary conversion of the relationship intensities (defined on an ordinal scale) into numerical coefficients (rij), and (ii) the aggregation of rij values through a weighted sum, which introduces an (undue) promotion to a cardinal scale with meaningful intervals [2]. In certain scenarios, the application of ISM can result in a distorted prioritization of ECs [4]. To address these conceptual concerns, this paper proposes a novel technique for prioritizing ECs based on Thurstone's Law of Comparative Judgment (LCJ) [3]. The proposed technique involves the following four steps: Translation of each row in the relationship matrix into a "local" ranking of ECs based on the intensity of their relationships with the CR of interest. For instance, the row corresponding to CR2 would result in EC2 > (EC1 = EC3). Translation of each ranking into pairwise comparisons. E.g., the previous ranking would be decomposed into three pairwise comparisons: (EC2 > EC1), (EC2 > EC3) and (EC1 = EC3). Aggregation of pairwise comparisons into a frequency matrix, incorporating weights based on the w_CR_i values [3]. Application of the LCJ to determine a final scaling of the ECs, which ultimately determines their prioritization. A real-world case study provides evidence that the proposed technique produces an unbiased solution. References 1. Franceschini, F. (2001). Advanced quality function deployment. CRC Press. 2. Franceschini, F., Galetto, M., Maisano, D. (2019). Designing performance measurement systems. Management for professionals, Springer, Cham. 3. Thurstone, LL. (1927). A law of comparative judgments. Psychological Review, 34(4): 273. 4. Franceschini, F., Maisano, D.A., Mastrogiacomo, L. (2022). Rankings and Decisions in Engineering. Springer International Publishing.