The correlation matrix placed over the “roof” of the HoQ (see area 6 of Figure 4.1) is triangular in shape and is situated over the area of product characteristics. This matrix allows us to describe the correlation existing among the various technical characteristics, through the use of univocal qualitative symbols representing the positive or negative trend and the intensity of each correlation. To represent these correlations the symbols indicated in Figure 4.6 are used. By highlighting the conflicting relationships (negative or highly negative), the matrix makes for speedy solutions and equitable trade-offs.
FIGURE 4.11 Competitiveness analysis and benchmarking. QFD represents an ideal envi-
ronment for quantifying the concepts of offered quality and perceived quality. (From Eureka, W.E. and Ryan, N.E. [1988], The Customer-Driven Company, ASI Press, Dearborn, MI; Franceschini, F. and Rossetto, S. [1995], Res. Eng. Design, 7, 270–278. With permission.)
58 Advanced Quality Function Deployment
The correlation matrix is used to determine which technical characteristics uphold one another and which are in conflict. The designation of positive or negative trends in correlations is based on the way each “how” influences the achievement of other “hows,” independent of the direction in which the target setting of the given characteristic moves. In positive correlations, a how upholds another how, whereas in negative correlations the two hows are in conflict.
Positive correlations help to determine which product characteristics are closely related. Thus, we can evaluate whether a contemporary modification of more than one specification can be obtained through the same action on the overall plan, and avoid possible duplicated work loads on company organizational structure, mini- mizing the energy absorbed by the design process.
Negative correlations, on the other hand, represent those situations that may probably require equitable trade-offs: these are the situations that should never be ignored. The unidentified compromises as well as the unresolved compromises inevitably lead to customer requisites not being satisfied. Compromises must be reached through adjustments in target values of the technical characteristics, which represent the system we intend to design.
In the example illustrated in Figure 4.10, the two characteristics of “lead dust generated” and “minimal erasure residue” are strongly related. When trying to produce a pencil that satisfies customer requirements by generating a minimal amount of lead dust, the residual traces on a sheet of paper after erasure will also be diminished.
REFERENCES
Akao, Y. (1988), Quality Function Deployment, Productivity Press, Cambridge, MA. Armacost, R.L., Componation, P.J., Mullens, M.A, and Swart, W.W. (1994), An AHP frame-
work for prioritizing customer requirement in QFD: an industrialized housing appli- cation, IIE Trans., 26(4), 72–79.
Brunswik, E. (1952), The Conceptual Framework of Psychology, University of Chicago Press, Chicago.
Conti, T. (1992), Come costruire la Qualità Totale, Ed. Sperling & Kupfer, Milano. Dahlgaard, C., Kristensen, D., and Kanji, G. (1994), Break down barriers between depart-
ments, in Advances in Total Quality Management, Kanji, G., Ed., Carfax, Sheffield, pp. 81–89.
Eureka, W.E. and Ryan, N.E. (1988), The Customer-Driven Company, ASI Press, Dearborn, MI. Franceschini, F. and Rossetto, S. (1995), QFD: the problem of comparing technical/engineer-
ing design requirements, Res. Eng. Design, 7, 270–278.
Griffin, A.J. and Hauser, J.R. (1993), Patterns of communication among marketing engineering and manufacturing — a comparison between two new product teams, Manage. Sci., 30(3), 360–373.
Hauser, J.R. and Clausing, D. (1988), The House of Quality, Harv. Bus. Rev., 66(3), 63–73. Hunter, M.R. and Van Landingham, R.D. (1994), Listening to the customer using QFD, Qual.
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Applying Quality Function Deployment 59
Leoni, G. and Raimondi, M. (1993), Un metodo per la misurazione della “customer satisfaction”, in Customer Satisfaction. Misurare e gestire la soddisfazione del Cliente, GRAMMA, Ed. UTET, Torino.
Sanchez, S.M., Ramberg, J.S., Fiero, J., and Pignatello, J.J. (1993), Quality by Design, in
Concurrent Engineering, Kusiak, A., Ed., John Wiley & Sons, pp. 235–250.
Tosalli, A., Conti, T., Pettigiani, A., and Pettigiani, M.G. (1990), La Qualità nel servizio, Bariletti Editori, Roma, pp. 209–214.
Urban, G.L. and Hauser, J.R. (1993), Design and Marketing of New Products, Prentice Hall, Englewood Cliffs, NJ, pp. 267–279.
Wasserman, G.S. (1993), On how to prioritize design requirements during the QFD planning process, IIE Trans., 25(3), 59–65.
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61
Supporting Tools of
Quality Function
Deployment
5.1 INTRODUCTION
Although many maintain that quality function deployment (QFD) methodology is a very useful communications tool, others point out that the technique, in its traditional form, does not come to terms in a sufficiently rigorous manner with some problems that arise when we endeavor to apply it within a complex industrial context.
This effectively represents one of the QFD shortcomings when it is applied in its more traditional form. It often appears to be somewhat “coarse” in its tentative efforts to reach a swift and simple solution to problems that are generally rather complex.
In this chapter we intend to point out some of these weak points found in traditional QFD methodology, and to indicate possible ways of solving them through its integration with several other design-supporting techniques.
Nowadays, QFD methodology is considered to be useful, particularly for its benefits in planning. In the very near future it could come to constitute the cohesive element within a group of instruments able to create an integrated environment for decisional aids in the field of design.
5.2 ASSIGNING LEVELS OF IMPORTANCE TO