18 Mar Complete?the?Week 2 Statistical Process Control Methods Worksheet, attached. To begin, measure the entire process over 10-12 periods of time (days, months, years). Use t
This assignment has a grading rubric, attached.
To learn how to apply SPCM to a process, continue the flowchart from Week 1 and identify variances within a process. You can find variances from the data identified in Week 1.
Complete the Week 2 Statistical Process Control Methods Worksheet, attached.
To begin, measure the entire process over 10-12 periods of time (days, months, years). Use time as your Metric.
Create a control chart including the baseline, upper control limits (UCL) and lower control limits (LCL).
NOTE: Feel free to use estimated time when real data is unavailable.
Submit your assignment using the Week 2 Statistical Process Control Methods Worksheet.
You may include your computations and graphs on the work sheet or attach them separately.
Resources
Microsoft® Word, PowerPoint®, Visio®, or Excel®
https://asq.org/quality-resources/control-chart, attached.
For online help in creating a control chart with upper control limits (UCL) and lower control limits (LCL) there are multiple websites that will walk you through the process. Search, How to create Control Charts.
OPS/574 v1
Statistical Process Control Methods
OPS/574 v1
Page 2 of 2
Statistical Process Control Methods
Process Evaluation
Evaluate your process using 1 of the following:
· Use the lean concept to find ways to eliminate waste and improve the process
· SPC or Six Sigma to reduce defects or variances in the process
<Write your evaluation here> |
Evaluation of Control Chart and Process Metrics
Complete the following in Excel:
· Calculate the defined process metrics including variation and process capability.
· Develop and display a control chart for the process.
Evaluate the control chart and process metrics using Statistical Process Control (SPC) methods. Determine whether the process could benefit from the use of Six Sigma, Lean, or other tools. (Include all calculation and charts.)
<Write your evaluation here> |
Executive Summary
Write a 700-word executive summary that includes the following:
· A summary of the Process Evaluation (using either Lean or SPC or Six Sigma)
· A summary of the Evaluation of Control Chart and Process metrics based on SPC methods
· A summary of your evaluation of whether the process would benefit from the use of Six Sigma, Lean, or other tools
· A description of the SPC project and recommendations for improvements
<Write your executive summary here> |
Copyright 2020 by University of Phoenix. All rights reserved.
Grading Rubric
image1.png
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Data Entry
Quality Tools | |||||||||||||||||||||||||
Control Charts | |||||||||||||||||||||||||
Description | Individuals Chart | ||||||||||||||||||||||||
This template illustrates a Statistical Process Control (SPC) chart. A detailed discussion of SPC charts can be found at www.ASQ.org | |||||||||||||||||||||||||
Learn About Statistical Process Control | |||||||||||||||||||||||||
Instructions | |||||||||||||||||||||||||
● | Select the correct subgroup size. When in doubt, select a subgroup size of one. Partial subgroups are not displayed. | ||||||||||||||||||||||||
● | Enter up to 200 data points in the cells provided. Do not enter values in the subgroup column. These cells update automatically to show the subgroup in which the data point is included. | ||||||||||||||||||||||||
Moving Range Chart | |||||||||||||||||||||||||
● | Identify any out of control conditions. Four tests are performed. Use the legend to identify the points corresponding to a particular test. | ||||||||||||||||||||||||
● | If a test looks for a proportion of points, only the offending point will be identified. For example, if eight points in a row are on one side of the centerline only the eighth point will be identified. | ||||||||||||||||||||||||
Learn More | ● | If a point fails more than one test, only one color will be displayed. | |||||||||||||||||||||||
To learn more about other quality tools, visit the ASQ Learn About Quality web site. | |||||||||||||||||||||||||
Learn About Quality | |||||||||||||||||||||||||
Three Sigma Limit | A single point outside the control limits | ||||||||||||||||||||||||
Two Sigma Limit | Two of three pts outside the two sigma limit | ||||||||||||||||||||||||
One Sigma Limit | Four of Five pts outside the one sigma limit | ||||||||||||||||||||||||
Average | Eight in a row on the same side of centerline | ||||||||||||||||||||||||
Control Chart Data | |||||||||||||||||||||||||
1.424 | Xbar/IMR Chart Avg | 10.076 | Xbar one sigma Upper Limit | 17.142 | Rbar one sigma Upper Limit | ||||||||||||||||||||
9.7581 | Range Chart Avg | 18.728 | Xbar two sigma Upper Limit | 24.525 | Rbar two sigma Upper Limit | ||||||||||||||||||||
8.650766415 | Rbar/d2 | 27.38 | Xbar three sigma Upper Limit | 31.909 | Rbar three sigma Upper Limit | ||||||||||||||||||||
125 | Number of samples | -7.228 | Xbar one sigma Lower Limit | 2.3745 | Rbar one sigma Lower Limit | ||||||||||||||||||||
1 | Subgroup size | -15.88 | Xbar two sigma Lower Limit | n/a | Rbar two sigma Lower Limit | ||||||||||||||||||||
125 | Number of subgroups | -24.53 | Xbar three sigma Lower Limit | n/a | Rbar three sigma Lower Limit | ||||||||||||||||||||
Sub Group | Data | Sub Group | Data | Sub Group | Data | Sub Group | Data | Sub Group | Data | Sub Group | Data | Sub Group | Data | Sub Group | Data | ||||||||||
1 | 15 | 26 | -5 | 51 | 24 | 76 | 32 | 101 | 18 | 126 | 151 | 176 | |||||||||||||
2 | 7 | 27 | 12 | 52 | 14 | 77 | 22 | 102 | 8 | 127 | 152 | 177 | |||||||||||||
3 | -2 | 28 | -6 | 53 | 10 | 78 | 18 | 103 | 4 | 128 | 153 | 178 | |||||||||||||
4 | -5 | 29 | -9 | 54 | -4 | 79 | 16 | 104 | -2 | 129 | 154 | 179 | |||||||||||||
5 | -10 | 30 | -8 | 55 | -4 | 80 | -4 | 105 | -8 | 130 | 155 | 180 | |||||||||||||
6 | 7 | 31 | 19 | 56 | 12 | 81 | 16 | 106 | 6 | 131 | 156 | 181 | |||||||||||||
7 | 2 | 32 | 11 | 57 | 4 | 82 | 10 | 107 | 0 | 132 | 157 | 182 | |||||||||||||
8 | -8 | 33 | 6 | 58 | 6 | 83 | 4 | 108 | -6 | 133 | 158 | 183 | |||||||||||||
9 | -7 | 34 | 0 | 59 | 0 | 84 | -2 | 109 | -12 | 134 | 159 | 184 | |||||||||||||
10 | -10 | 35 | 4 | 60 | -12 | 85 | -8 | 110 | -18 | 135 | 160 | 185 | |||||||||||||
11 | -2 | 36 | 24 | 61 | 9 | 86 | 16 | 111 | 12 | 136 | 161 | 186 | |||||||||||||
12 | -7 | 37 | 6 | 62 | -7 | 87 | 9 | 112 | 6 | 137 | 162 | 187 | |||||||||||||
13 | -11 | 38 | 6 | 63 | -11 | 88 | 1 | 113 | 2 | 138 | 163 | 188 | |||||||||||||
14 | -15 | 39 | 1 | 64 | -17 | 89 | -6 | 114 | -2 | 139 | 164 | 189 | |||||||||||||
15 | -20 | 40 | -6 | 65 | -22 | 90 | -12 | 115 | -8 | 140 | 165 | 190 | |||||||||||||
16 | -3 | 41 | 6 | 66 | 15 | 91 | 24 | 116 | 18 | 141 | 166 | 191 | |||||||||||||
17 | -8 | 42 | -4 | 67 | 9 | 92 | 18 | 117 | 8 | 142 | 167 | 192 | |||||||||||||
18 | -12 | 43 | -5 | 68 | 3 | 93 | 14 | 118 | 4 | 143 | 168 | 193 | |||||||||||||
19 | -18 | 44 | -10 | 69 | -3 | 94 | 9 | 119 | -2 | 144 | 169 | 194 | |||||||||||||
20 | -19 | 45 | -12 | 70 | -9 | 95 | -5 | 120 | -8 | 145 | 170 | 195 | |||||||||||||
21 | 4 | 46 | 23 | 71 | 25 | 96 | 19 | 121 | 10 | 146 | 171 | 196 | |||||||||||||
22 | -3 | 47 | 17 | 72 | 14 | 97 | 13 | 122 | -6 | 147 | 172 | 197 | |||||||||||||
23 | -8 | 48 | 11 | 73 | 5 | 98 | 7 | 123 | -5 | 148 | 173 | 198 | |||||||||||||
24 | -14 | 49 | 9 | 74 | 2 | 99 | 1 | 124 | -7 | 149 | 174 | 199 | |||||||||||||
25 | -19 | 50 | -5 | 75 | -6 | 100 | -5 | 125 | -17 | 150 | 175 | 200 |
Data Entry
-24.5324516129 | 27.3804516129 | 15 | 1.424 | -7.2281505376 | 10.0761505376 | -15.8803010753 | 18.7283010753
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