The QFD tables allow us to obtain an integrated and structured overall view of the project, of the requisites to be satisfied, and of their relationships to the characteristics of the particular product or service. QFD maps, in particular, show profiles of the
functions compared with those proffered by competitors (technical evaluation) lim-
ited to the upper limits of performance.
However, QFD tables do not explicitly present the various alternatives that can
be used to “conceive” the single product functions pi. In other words, although the
QFD modules allow us to get a clear enough picture of the requisites and the functions with which the product or service must be endowed, no emphasis is placed on the alternative ways of carrying out a particular characteristic pi. Using disparate strate-
gies, of a technical nature as well as of an economic nature, one can, in point of fact, satisfy the totality of requirements expressed by the customer.
This observation suggests the introduction of a third dimension, perpendicular to the plane constituting customer and product requirements, able to determine alternative ways of attaining the various single product or service characteristics (see Figure 10.3).
In definition:
• P = {p1, …, pm} the set of technical product or service characteristics.
• Ai = {ai1, …, ain} the set of technological alternatives that could be chosen
to fulfill the requirement pi with i = 1, …, m.
• Ri = {r1, …, rk} the set of criteria (coinciding with customer requirements),
which intervene in the evaluation of the alternatives for the characteristic
pi with i = 1, …, m and Ri⊆ R (the set of criteria), each having its own
evaluation scale (not necessarily numerical).
For each Ai, we encounter the problem of selecting a technological alternative
ai* to best satisfy the preferences expressed on the criteria in Ri by the customer
(decision maker).
134 Advanced Quality Function Deployment
The set A* showing the selected alternatives, for each p
i, determines the “tech-
nological profile of product alternatives” expressed on the criteria in R.
As is immediately evident, we once again face an MCDA problem (the maximum function is taken with respect to the system of customer preferences) [Ostanello, 1985; Roy, 1985].
It must be noted that the problem we have just mentioned, although making use of the same instruments utilized to determine the profile of a product compared with competitive items (see Chapter 6), is substantially different in nature from the latter.
FIGURE 10.3 Product planning plans for the selection of technological alternatives.
A ai A R ai i i R a i m ai Ai i i * * max , , = ∈
( )
=( )
∀ = … ∈ 1 ,Setting Up Sizable Projects — Constraints of Quality 135
The problem, in this case, is the identification of the most feasible technological solution able to carry out a certain technical performance.
From the point of view of the sequence of activities to be developed, we first determine the technical parameters to be assigned to the various technological alternatives identified when compared with the competition (see Chapter 6). At a successive stage we shall determine the most suitable technologies to be utilized.
An example may be useful to clarify the concept [Telettra, 1988a]. For the
requisite p8 (programming language), we are faced with the problem of choosing
the type of memory format used to codify the programs (logics–sequences–loops) drawn up by the user. The languages examined were: list of instructions, functional blocks, and ladders, respectively.
The criteria that concurred in selecting the alternatives were (Table 10.1):
• r5 MMI (editor)
• r9 development and setup times
• r4 simplicity of usage of the software development tools (debugger, etc.)
• r6 compatibility among different languages
The technological alternatives identified were:
a1) An ASCII format for the three languages
a2) A compact format derived from the list of instructions for all three languages
a3) A different format for the three languages
The evaluations of the technological alternatives available for the various criteria for requisite p8 are shown in Table 10.1.
The analysis of each single product characteristic can be rapidly extended to all the other remaining characteristics. With reference to Figure 10.3, it is possible to identify three types of plans: plan (A, P) concerning product profile, plan (A, R) concerning the selection of alternatives, and plan (R, P) concerning the “canonical” house of quality (HoQ).
TABLE 10.1
Selection of Technological Alternatives for the Programming Language Characteristic
Criteria
Alternatives
a1 a2 a3
r5: man-machine interface (editor) High Medium High
r9: development and setup times (man/month) 57 53 75
r4: usage of the software development tools (debugger, etc.) Medium Good High
r6: compatibility among different languages Yes Yes No
136 Advanced Quality Function Deployment
Each one of the plans we have determined is able to supply useful indications concerning the activities of design planning. In greater detail, plan (A, P) allows us to identify all the selected alternatives and to confront the various development strategies (contemporary evaluation of various alternative profiles). Plan (A, R)
allows us to constantly check the evaluations of the alternatives, for each pi, in
relation to the different selection criteria.
REFERENCES
Baccalaro, W. and White, J. (1992), QFD and Quality in Design: Integrating QFD, DOE, Design Review and FMEA, First European Conference on Quality Function Deployment, Milano.
Conti, T. (1989), Process management and quality function deployment, Qual. Prog., 22(5), 35–42.
Crow, K.A. (1992), Seminar on Concurrent Engineering, DRM Associates, Rome. ESA–BSSC (1991), ESA Software Engineering Standards, ESA PSS-05-0, Issue 2. Fiegenbaum, A.V. (1983), Total Quality Control, 3rd ed., McGraw-Hill Book, New York. Franceschini, F. and Mattiacci, T. (1990), PRODAS (Process Optimization and Data Acquisition
System): Un sistema per la gestione integrata dei servizi energetici, L’elettrotecnica, 77(10), 945–952.
Hill, A. (1992), New Product Introduction through QFD in a Total Quality Environment, First European Conference on Quality Function Deployment, Milano.
Ostanello, A. (1985), Outranking Methods in Multiple Criteria Decision Methods and
Applications, Fandl, G. and Spronk, J., Eds., Springer-Verlag, Berlin, pp. 41–60.
Pugh, S. (1991), Total Design — Integrated Methods for Successful Product Engineering, Addison-Wesley, New York.
Rossi, F. (1985), Appunti su Qualità e normativa per il SW, Telettra serie Qualità e Affidabilità. Roy, B. (1985), Methodologie multicritere d’aide à la decision, Ed. Libraire Economica, Paris. Schiani, E. (1988), Specifica Funzionale del sottosistema MMI (Man Machine Interface) per
il livello 1 del progetto PRODAS.
Sullivan, L. (1986), Quality function deployment, Qual. Prog., 19(6), pp. 39–50. Telettra, SpA (1988a), Normative per la Qualita’ del SW. Standard 20 - V1.1. Telettra, SpA (1988b), Progetto PRODAS alternative di progetto.
Telettra, SpA (1990), La specificazione del SW, 1.0.
Zucchelli, F. (1992), La Qualità Totale e il QFD, First European Conference on Quality Function Deployment, Milano.
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