Page 177 - Design for Six Sigma a Roadmap for Product Development

150 Chapter Five

1. The “generation” activity can be enriched by the deployment of
design axiom 1 and its entire derived theoretical framework, which
calls for functional requirements independence. This deployment
will be further enhanced by many TRIZ methodology concepts to
resolve design vulnerabilities where applicable.
2. The “selection” activity can be enhanced by the deployment of axiom
2, which calls for design simplicity.

The controlled convergence method uses comparison of each alter-
native solution entity against a reference datum. Evaluation of a sin-
gle solution entity is more subjective than objective. However, the
method discourages promotion of ideas based on opinion and thus
promotes objectivity. The controlled convergence method prevents
adverse features and eliminates weak concepts, thereby facilitating
the emergence of new concepts. It illuminates the best solution entity
as the one most likely to meet the constraints and requirements of the
customer as expressed by the design specification, and the one which
is least vulnerable to immediate competition.
The development of the concepts through the combination of solu-
tion alternatives per functional requirement can be identified by a
matrix technique called the synthesis matrix. In this matrix, the func-
tional requirements (FRs) are listed in the rows and the solution alter-
natives (the design parameters) are laid down in the columns. At this
step, the design parameters are usually known at a hierarchal level
equivalent to components, subsystem, and subprocesses or in terms of
physical effects (e.g., electric field). However, this knowledge is not
detailed at this stage. The functional requirements need to be listed in
the order of their hierarchy by the team, to the best of their knowledge
at this step, and should be grouped according to their type of input
(energy type, material type, information type).
The concepts are synthesized and generated from all possible feasi-
ble combinations of all possible design parameters (DPs) per func-
tional requirement (FR) in the synthesis matrix. A feasible design is
identified by connecting all possible solutions using arrows between
the design parameters. The arrows can be connected only when the
team is technically confident about the functional and production
feasibility. For example, in Fig. 5.10, two concepts can be identified.
Solutions for which the number of arrows is less than the number of
rows are infeasible situations.
In conducting this exercise, the team will identify all possible feasi-
ble design solutions. In the next step, guided by their knowledge and
DFSS algorithm, the team should concentrate only on promising solu-
tions. The challenge here is to ensure that the physical-functional
compatibility and other constraints are met and the appropriate flow