Many manufacturing situations, for example, the production of such large and complex items as aircraft or machines, exhibit a learning effect in which the production time per unit decreases as more units are produced. This is often modeled by a power curve,

y=axb,

where a and b are constants. Suppose that the accompanying data on production times for the first ten units produced were collected from a new project at Glasgow Machine Tool. Develop a model for estimating the power curve to minimize the sum of the squared deviations of the errors. Use nonlinear optimization to find the parameters.

Unit Production Hours 1 3161 2 2720 3 2615 4 2278 5 2028 6 2193 7 2249 8 2268 9 1994 10 2000

The model is

y=( )x^(- )

(Round to two decimal places as needed.)