Answered: Analyze Filling Line Problems Using…

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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Assignment: Analyze Filling Line Problems Using Control Charting Attached Files: File Filling line example for X-bar & control chart.xlsxOpen this document with ReadSpeaker docReader (13.354 KB) Using the provided data, calculate the control limits (X-bar and r-chart, Capability Index, create a control chart, and calculate the percentage of units that are expected to be out of spec (z-value). Show your work A quick way to do the percents part of the filling line problem (you know, the percent underfilled, the percent overfilled, etc.), is to use Excel's norm.dist function rather than looking it up on a printed Z table. Use the norm.dist excel function with the LSL in the first position in the parameter list. Norm.dist gives you the left side return from the Z table. "Excel offers you the NORM.DIST statistical function for working with normal distributions. The NORM.DIST function calculates the probability that variable X falls below or at a specified value" (https://www.dummies.com/software/microsoft-office/excel/how-to-use-the-norm-dist-function-in-excel/ ... the most succinct explanation I've found online).

Observations
Sample # 8am 9am 10am 11am noon
#1
14
10
9
9
11
#2
12
10
10
8
12
#3
13
11
12
10
14
#4
9
12
9
7
# 5
11
11
10
9
#6
10
9
9
8
#7
9
10
11
11
9
11
11
LO CO
9
1pm 2pm 3pm 4pm
9
13
10
9
12
9
9
12
10
10
10
9
8
10
10
9
8
56
10
12
10
9
8
8
X
10.50
10.00
11.40
10.00
9.60
9.60
9.40
Average = 10.071
10
9
11
9
9
5pm
11
8
10
13
9
12
10
R
5
4
4
6
3
4
3
4.143

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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