Complete the attached MS Excel file (both worksheets / tabs) as your assignment this week. No APA formatted report required; just complete the template's questions.

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assignmentone.xlsx

Part 1 of 2

Week Two Assignment
Assignment: Part 1 - Is my manufacturing process in control? (Statistically speaking…)
Background on Statistical Controls in Manufacturing: A state of statistical control is defined as a process with a constant mean and variance that is not changing over time. Generally speaking, the upper and lower control limits are set at ± three standard deviations from the mean. If a normal probability distribution is assumed, these control limits will include 99.74 percent of the random variation observed.
UCL = Average + 3*Standard-Deviation (Upper Control Limit)
CL = Average (Center Line)
LCL = Average - 3*Standard-Deviation (Lower Control Limit)
Activity: For our hypothetical single-port yogurt filing machine (shown below). See the filing results of the first 100 cups of yogurt and their actual weight after filing. Compute the UCL, CL, and LCL to determine if your process is in control. As a reminder, your process is "in control" if you nearly all of the products produced (99.74% or higher) are within the Upper Control Limit (UCL) and Lower Control Limit (LCL) values. Otherwise, your process is not in control and needs to be triaged.
Sample # Actual Fill (oz) Within Control Limits? Statistical Calculations
1 8.028 FALSE
2 7.986 FALSE Average = oz Tip: Reminder that to calculate the average, you can use Excel's AVERAGE function. Just add the function and select all of the actual fill examples. The same is true with standard deviation, by using Excel's STDEV formula. Select the same actual fill examples.
3 7.985 FALSE Standard Deviation = oz
4 8.036 FALSE
5 8.018 FALSE
6 7.937 FALSE UCL = oz
7 8.026 FALSE Center Line = oz
8 8.050 FALSE LCL = oz
9 7.920 FALSE
10 7.974 FALSE
11 7.890 FALSE Is this process in control? (Yes/No) and Why?
12 8.032 FALSE
13 7.948 FALSE
14 8.013 FALSE Should I keep making yogurt?
15 7.943 FALSE
16 8.069 FALSE
17 7.918 FALSE
18 7.650 FALSE
19 7.895 FALSE
20 7.959 FALSE
21 8.030 FALSE
22 7.845 FALSE
23 7.952 FALSE
24 8.036 FALSE
25 8.004 FALSE
26 7.861 FALSE
27 7.899 FALSE
28 8.036 FALSE
Graph Data (automatically pulls entered values) 29 8.067 FALSE
UCL CL LCL 30 8.037 FALSE
1 0 0.000 0 31 7.959 FALSE
100 0.000 0.000 0.000 32 7.700 FALSE
33 7.844 FALSE
34 7.990 FALSE
35 7.949 FALSE
36 7.991 FALSE
37 7.986 FALSE
38 7.947 FALSE
39 7.890 FALSE
40 8.071 FALSE
41 8.063 FALSE
42 8.048 FALSE
43 7.900 FALSE
44 8.067 FALSE
45 7.834 FALSE
46 7.946 FALSE
47 7.925 FALSE
48 7.977 FALSE
49 8.007 FALSE
50 8.045 FALSE
51 7.875 FALSE
52 7.928 FALSE
53 7.869 FALSE
54 8.041 FALSE
55 7.849 FALSE
56 7.859 FALSE
57 7.888 FALSE
58 7.887 FALSE
59 7.965 FALSE
60 7.895 FALSE
61 7.964 FALSE
62 7.979 FALSE
63 7.952 FALSE
64 8.003 FALSE
65 8.028 FALSE
66 7.995 FALSE
67 7.903 FALSE
68 7.839 FALSE
69 8.034 FALSE
70 7.827 FALSE
71 8.010 FALSE
72 7.826 FALSE
73 7.934 FALSE
74 7.936 FALSE
75 7.650 FALSE
76 7.965 FALSE
77 7.963 FALSE
78 7.911 FALSE
79 8.072 FALSE
80 7.923 FALSE
81 7.961 FALSE
82 7.929 FALSE
83 7.847 FALSE
84 7.866 FALSE
85 7.841 FALSE
86 8.065 FALSE
87 7.963 FALSE
88 7.858 FALSE
89 7.954 FALSE
90 7.978 FALSE
91 8.022 FALSE
92 7.834 FALSE
93 8.022 FALSE
94 7.875 FALSE
95 8.006 FALSE
96 8.012 FALSE
97 7.975 FALSE
98 7.916 FALSE
99 8.055 FALSE
100 7.837 FALSE

Yogurt Fill in Ounces

8.0281736737680873 7.9861588451169245 7.9846191970792937 8.0364573021020096 8.0184423894555596 7.9366937883180242 8.025738956149981 8.0501431232677145 7.9198610915878769 7.9737775522306995 7.890053330381952 8.0320336664575684 7.9478173692205685 8.0131653011324655 7.9432003970486145 8.0685101142754352 7.9179586141594918 7.65 7.8949990807378416 7.9594338556283004 8.0296066595894597 7.8445420747916463 7.9519425458344219 8.0360329293196227 8.0035494900103572 7.8610744660617895 7.899233642161728 8.03585850213166 8.0665533652480335 8.0368954119424316 7.9587304894731314 7.7 7.8435359590405582 7.9898029565495907 7.9487266490670656 7.9907430626068789 7.9857380824479014 7.9468174978560819 7.8896638780722581 8.0706745935935782 8.062999596936816 8.0478656640008417 7.9 8.0666788965712648 7.8344699904575075 7.9459236414269299 7.9252830316579868 7.9766981003676412 8.0074815796778296 8.0449111344826729 7.8748164534288154 7.928393746545388 7.8694911493210897 8.0410221763514969 7.8485725529156118 7.8589881575563627 7.8880615198384074 7.8868253106984083 7.9650250968305727 7.8948599592640383 7.9643067389095972 7.9794055706977352 7.9515281476759965 8.0033058613496131 8.0284574786424976 7.9945994755256065 7.9032096829952199 7.8390235759585849 8.0343593062862979 7.8271361481950752 8.0102463192870612 7.8255513331225117 7.9335959810887662 7.9361700606446632 7.65 7.9647472332234353 7.9632008432100303 7.9106715564262959 8.0715018625874606 7.9230813298074461 7.9605449987698549 7.9294806914746578 7.8472621574071235 7.8656399820822491 7.8410947501254711 8.064949321866818 7.9626724777062208 7.857555709307726 7.9536272543285227 7.978182749197301 8.0222101477150254 7.8338476368459409 8.0224640809551548 7.8749894496785826 8.0057249686272982 8.0118473243159816 7.9747503804735587 7.9159683692246769 8.0551888545321546 7.8367598115535229 UCL 1 100 0 0 CL 1 100 0 0 LCL 1 100 0 0

Sample #

Weight of Cup (oz)

Part 2 of 2

Assignment: Part 2 - How do I control my production?
Background: Once we get the process fixed (i.e., in control), we should still regularly monitor it's performance. Here's how: Remember that our quality measure is the amount (weight) of yogurt in each cup -- not too much or you waste money and make a mess, and not too little or customers (and the FDA) will be upset. Weight is a continuous variable measured very accurately in ounces. We need to be concerned not just with the average weight, but also how well our machine is performing. To do that, we'll need an X-bar chart and an R-chart.
Question: What is "n" (the sub-group size), in the quality sampling recorded below? n =
Sample # Time Cup #
1 2 3 4 5 6 7 8
1 8:00am 8.005 8.200 7.938 8.012 7.941 7.954 7.810 8.088
2 10:00am 7.821 8.180 8.069 7.854 8.197 8.152 8.089 8.155
3 12:00pm 7.989 7.878 7.914 8.151 8.007 7.800 8.116 7.803
4 2:00pm 8.147 8.164 8.167 7.862 7.952 7.976 7.838 7.965
5 4:00pm 8.038 8.082 7.892 7.988 7.851 7.839 8.056 8.176
6 6:00pm 8.142 8.073 8.193 8.017 8.111 8.046 8.168 8.060
Activity: Next, calculate the Sample Averages based on the above samples. This will ultimately help you calculate X-bar. Then calculate the range within each sample group. To calculate the range in a sample group, use the following formula:
Range = Maximum values of selected cells - Minimum values of selected cells
MAX(cell range)-MIN(cell range)
Sample Average (X-bar) Range within Sample Activity: Once you calculate the sample average and range within the sample, you can calculate the Overall Averages for both. This gives the X-double bar and R-bar, which we need for our X-Bar and R-Bar charts.
Overall average =
Activity: In order to create the charts, we need to populate the constants below. You can find these in our textbook in Table 9.1
Activity: Use the formulas below to calculate the Upper Control Limit (UCL), Center Line (CL), and Lower Control Limit (LCL) values. This will automatically populate the X-Bar Chart below.
UCL =
CL =
LCL =
Activity: Use the formulas below to calculate the Upper Control Limit (UCL), Center Line (CL), and Lower Control Limit (LCL) values. This will automatically populate the R Chart below.
UCL =
CL =
LCL =
Is this process in control? (Yes/No) and Why? Should I keep making yogurt?
Graph Data (automatically pulls entered values)
X-bar UCL CL LCL
1 0.00 0.00 0.00
8 0.00 0.00 0.00
R chart UCL CL LCL
1 0.00 0.00 0.00
8 0.00 0.00 0.00

X-bar Chart

1 2 3 4 5 6 UCL 1 8 0 0 CL 1 8 0 0 LCL 1 8 0 0

Sample #

Weight of yogurt cup (oz)

R Chart

1 2 3 4 5 6 UCL 1 8 0 0 CL 1 8 0 0 LCL 1 8 0 0

Sample #

Range of Weight of yogurt cup (oz)

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