Page 203 - Design for Six Sigma a Roadmap for Product Development

176 Chapter Five

consumption, maintenance, and repair. The aim is to minimize envi-
ronmental impact, including strategic level of policy decision making
and design development.
The team should take advantage of, and strive to design into, the
existing capabilities of suppliers, internal plants, and assembly lines.
It is cost-effective, at least for the near term. The idea is to create
designs sufficiently robust to achieve Six Sigma design performance
from current capability. Concurrent engineering enables this kind of
upside-down thinking. Such concepts are applied in the DFSS algo-
rithm to improve design for manufacturing, assembly, and service.
These key “design for” activities are well known, including the
Boothroyd-Dewhurst design for assembly, and a spectrum of design for
manufacture and design for service methodologies. The major chal-
lenge is implementation. Time and resources need to be provided to
carry out the “design for” activities.
A danger lurks in the DFX methodologies that can curtail or limit
the pursuit of excellence. Time and resource constraints can tempt
DFSS teams to accept the unacceptable on the premise that the
shortfall can be corrected in one of the subsequent steps—the “second
chance” syndrome. Just as wrong concepts cannot be recovered by
brilliant detail design, bad first-instance detail designs cannot be
recovered through failure mode analysis, optimization, or tolerance
design.

5.12 Tolerance Design and Tolerancing
(DFSS Algorithm Step 11)
The purpose of the tolerance design step is to assign tolerances to the
part, assembly, or process, identified in the functional and physical
structures, based on overall tolerable variation in FRs, the relative
influence of different sources of variation on the whole, and the cost-
benefit trade-offs. In this step, the DFSS team determines the allow-
able deviations in DPs values, tightening tolerances and upgrading
materials only where necessary to meet the FRs. Where possible, tol-
erances may also be loosened.
In the DFSS algorithm, this step calls for thoughtful selection of
design parameter tolerances and material upgrades that will be later
cascaded to the process variables. Selection is based on the econom-
ics of customer satisfaction, the cost of manufacturing and production,
and the relative contribution of sources of FR variation to the whole
design project. When this is done, the cost of the design is balanced
with the quality of the design within the context of satisfying cus-
tomer demands. By determining which tolerances have the greatest
impact on FR variation, only a few tolerances need to be tightened,