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Simulation and optimization techniques can provide Design for Six Sigma (DFSS) practitioners with reduced reliance on physical prototypes, rapid time-to-market, minimal defects and post-design rework. These advantages lead to quantifiable benefits within the product development life-cycle, in terms of time and cost. Through one case study, this paper will provide Six Sigma, Process Excellence and Lean practitioners with the rationale for spreadsheet simulation and optimization in DFSS initiatives. Discussion topics include the role of simulation and optimization in the DMADV methodology, disadvantages of not quantifying uncertainty in DFSS projects, differences between deterministic and stochastic optimization, and tradeoff considerations when running optimizations. Practical techniques for efficiently identifying robust, high quality solutions are demonstrated through the use of Monte Carlo simulation and optimization.
Luce et al. (Sun,) studied this question.