Title :
Sensitivity analysis for robust parameter design experiments
Author_Institution :
Dept. of Eng. Manage. & Syst., Dayton Univ., OH, USA
Abstract :
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.
Keywords :
noise; process design; product design; sensitivity analysis; design factor; design solution; noise condition; noise effect; noise source; operating environment; process noise immunity; product noise immunity; robust parameter design experiment; sensitivity analysis; Bidirectional control; Communication networks; Computer networks; Context; Monte Carlo methods; Random variables; Sensitivity analysis; Stochastic processes; Stochastic systems; Telecommunication network reliability;
Conference_Titel :
Simulation Conference, 2005 Proceedings of the Winter
Print_ISBN :
0-7803-9519-0
DOI :
10.1109/WSC.2005.1574287
