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. Click the icon to view the production times data. The model is y ----))
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. Click the icon to view the production times data. The model is y ----))
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![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 = ax , 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.
Click the icon to view the production times data.
The model is y=(x-D
(Round to two decimal places as needed.)
Get more help
Production Times Data
Unit Production Hours
1
2
3
4
5
6
7
8
9
10
Print
3,211.00
2,720.00
2,615.00
2,278.00
2,028.00
2,193.00
2,249.00
2,268.00
1,994.00
2,000.00
Done
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[]
Clear all
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Transcribed Image Text: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 = ax , 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.
Click the icon to view the production times data.
The model is y=(x-D
(Round to two decimal places as needed.)
Get more help
Production Times Data
Unit Production Hours
1
2
3
4
5
6
7
8
9
10
Print
3,211.00
2,720.00
2,615.00
2,278.00
2,028.00
2,193.00
2,249.00
2,268.00
1,994.00
2,000.00
Done
X
[]
Clear all
Check answer
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