When designing a complex mechanical system there is always considerable emphasis on reducing the time spent determining the best design. Understanding factors that contribute to the performance of the system as rapidly as possible is very important. Supersaturated statistical designs (SSDs) offer a potentially useful way to investigate many factors with very few experiments. SSDs investigate m factors with n experiments, where m > n - 1. In this paper, we demonstrate the use of a SSD in the detailed design phase of a turbine engine. Three SSDs and three orthogonal two-level factorial experiments were used as screening experiments. The results show that SSDs are a reasonable analysis choice, since few active factors are missed.
|Original language||English (US)|
|Number of pages||11|
|State||Published - Jan 2007|
- Factorial design
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Industrial and Manufacturing Engineering