# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 X -0.3 2.5 0.6 0.8 0.8 0.6 -0.1 1.6 0.1 0.4 0.7 3 -0.1 1.3 0.1 0.5 0 1 0.5 0.2 Y 1.9 2.6 2 1 1.9 2.1 1.8 1.6 1.1 1.9 1.9 3.4 1.6 1.5 1.3 2.2 2.2 1.8 1.4 1.5
# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 X -0.3 2.5 0.6 0.8 0.8 0.6 -0.1 1.6 0.1 0.4 0.7 3 -0.1 1.3 0.1 0.5 0 1 0.5 0.2 Y 1.9 2.6 2 1 1.9 2.1 1.8 1.6 1.1 1.9 1.9 3.4 1.6 1.5 1.3 2.2 2.2 1.8 1.4 1.5
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Use the data provided on Canvas. In automotive assembly processes, automation cannot always guarantee the dimensional accuracy of a car assembly as required by the design specification. Thus, some skillful workers will visually inspect those assembled car bodies and conduct manual adjustments when necessary. These workers are called "Fitter" in the automotive industry. This scenario is illustrated in the following

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Homework 3 Dataset.xlsx
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Transcribed Image Text:Use the data provided on Canvas. In automotive assembly processes, automation cannot always guarantee
the dimensional accuracy of a car assembly as required by the design specification. Thus, some skillful
workers will visually inspect those assembled car bodies and conduct manual adjustments when necessary.
These workers are called "Fitter" in the automotive industry. This scenario is illustrated in the following
figure.
Automatic assembly
process
X
P₁
Fitter
Y
P₂
One critical quality characteristics on a car assembly were measured at both P₁ (before fitter) and P₂ (after
fitter). The data are labeled as X and Y, respectively, and 20 measurements are shown below. Please use
the risk adjustment method to test if X and/or Y are in control. Please show X chart, Y chart and Z chart.
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