Sensitivity analysis for robust parameter design experiments

Robust parameter design experiments lead to products and processes that are insensitive to the effects of noise. These experiments reveal the interaction of the noise sources with design or control factors usually allowing creation of products that are relatively immune to noise. Finding truly optimal settings for design factors depends on the noise in the lab being representative of the actual operating environment and assumes potential product users all see the same noise conditions. This paper shows how basic design solutions can be shaped when multiple populations see different noise conditions and when typical assumptions on noise sources are violated.