Abstract: This paper presents a new approach to rationally allocate means and tolerances in
engineering systems at the design stage. Features of second-moment methods and Design for
Six Sigma methods are combined. Either point or global variance methods may be invoked to
model the uncertainty in the design variables. Shortcomings of Taguchi’s expected loss
function and the need to integrate over the failure region in probabilistic methods are obviated.
Multiple responses, each with any of the performance metrics including target-is-best, smalleris-best
and larger-is-best, are handled. The novelty of the approach is that cost or quality may
serve as an objective with the other serving as a constraint in the optimization process. The
impact of the method is that it reinforces quality concepts from Six Sigma design while
ensuring that robustness is maximized. Two diverse case studies justify the methodology.
Keywords: Quality, cost, variance decomposition, multiple responses, Six Sigma, robustness,
optimization