Operation Management

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Homework #5

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Operation Management
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MEM Program

Operations Excellence

Due: Start of Class 02/17/20

Worth 10 Points

Case Study Problem:

Using Excel, build a queuing model of the Rosemount Vortex Flowmeter plant (like the one we completed in class for Penny Fab Two). Please use the starter spreadsheet. If you need additional fields or want new assumptions, feel free to add them in. The queuing model should include the raw processing time, failures, set-ups, rework, variability, the impact of Magic/Magnetic, and anything else you think is important. You will need to spend some time thinking about how to best model the flow lab. However, the model does not have to include the impact of batch moves or the impact of technicians. The model should include, as output, the average WIP and average CT.

Please post a copy of your final spreadsheet. Please make sure your name (or initials) is in the name of the file and your name is in the spreadsheet.

In addition to the spreadsheet, you should include a brief write-up:

a) an explanation of the model and any assumptions you made

b) the strengths and weaknesses of the model

c) how realistic you think the model is

d) Insights and conclusions from the model as to how cycle time could be reduced. If you discovered something different than after your first reading of the case, it would be interesting to point that out.

Please be sure to check that the model behaves correctly to changes in the input and makes sense intuitively. Hint: Please make sure your calculations do not show negative cycle stock or WIP numbers. If initial calculations show this, make reasonable assumptions to avoid the problem.

2

>Rosemount

ata

reakdowns

achines

R

ff Process Time

V

Eff Var Eff SCV Eff Process time Eff Var Eff SCV Eff Process Time Eff Var Eff SCV Eff Process Time

Machine

.2

2

5

9%

0.0

1

0

0.1

1 1 0.26

0.26

5

0.02 0.28 0.30 0.28

.89

1

0.03 8

.0

0.01 5

0.17 99.6% 1 1 0.02

0.02

0.05 0.00

0.05 1.88

19.59

1

8

.0

0 0 5 40 0.17 0.17 99.6% 1 15 0.03 0.00

0.03

0.03

6

0.25 0.03 0.00 0.29 0.03 0.29

37.93

A 1

0.29 16

1 20

0.5

15 15 0.31

5

73

0.39

0.65 0.39 0.65

2.56

B 1 0.31

16 100% 9,999,999 0.08 0.04 1 20 0.5 0.5 98% 15 15 0.31 0.05

0.32

0.65

0.40 0.07 0.42 0.40 0.42

2.48

C 1

100% 9,999,999 0.06 0.03 1 20 0.5 0.5 98% 15 15 0.24

0.25

42

0.31

0.31

1.58 0.31 1.58

3.19

D 1 0.15 0.31 16 100% 9,999,999 0.05 0.03 1 20 0.5 0.5 98% 15 15 0.15 0.10

0.15

0.20

2.60 0.20 2.60

4.88

E 1

0.17 16 100% 9,999,999 0.07 0.03 1 20 0.5 0.5 98% 15 15 0.18 0.03

0.18

0.25

0.25 0.04 0.62 0.25 0.62

4.06

1 0.03 0.006 8

0 0 1 40 0.17 0.17 99.6% 15 1 0.03 0.00 0.04 0.03 0.0002 0.20 0.03

0.20 0.03 0.00 0.31 0.03 0.31

28.86

1 0.023 0.006 8 99% 100.0 0 0 1 40 0.17 0.17 99.6% 1 1 0.02 0.00 0.07 0.02 0.0002 0.28 0.02

0.28 0.02 0.00 0.29 0.02 0.29

42.87

1

0.006 8 99% 100.0 0 0 1

0.0001 0

1 1 0.02 0.00 0.16 0.02

0.16 0.02

0.16 0.02 0.00 0.17 0.02 0.17

66.01

1 0.015 0.006 8 100%

0 0 1 9999999 0.0001 0 100.0% 1 1 0.02 0.00 0.16 0.02 0.0000 0.16 0.02 0.00004 0.16 0.02 0.00 0.16 0.02 0.16

66.67

ion Data

Product

1 A M

1 1 0.01 48 9

0.8 0.15

1 A V

5 25 0.09 17 4

0.28 0.07

2 A M 6.668 5 25 0.01 12 4

0.20 0.07

3 A M 6.668 5 25 0.01

4

0.07

3 B M 6.668 1 1 0.01

8

4 B M

1 1 0.02

7

4 B M

1 1 0.01 22 7

0.37 0.12

4 B V

7 49 0.10 12 4

0.20 0.07

5 C M 16.67 1 1 0.02 54 6

0.10

5 C M 16.67 1 1 0.02 41 6

0.10

5 C V

7 49 0.15 10 3

0.17 0.05

5 C V

8 64 0.15 10 4

0.17 0.07

6 D M 10.002 1 1 0.01 40 6

0.10

6 D V

8 64 0.16 8 3

0.13 0.05

6 D V

7 49 0.13 7 3 1000.20 0.12 0.05

7 E M 10.002 1 1 0.01 23 6 290.06

0.10

7 E M 16.67 1 1 0.02 22 6

0.37 0.10

7 E V

3 9 0.07 5 3

0.08 0.05

1.00

13769.42

Input

D Natural From

B From Set Ups From Re-work** Summary
Operation M Raw Processing Time (hrs) Natural Std Dev (hr) Hrs/day Yield Jobs Between Rework Set Up Time (hrs) Set up SD (hrs) Units b/n Setups MTTF (hrs) MTTR (hrs) MTTR-

V A Avail Batch In Batch Out E Eff Var Eff S

C Eff Process time Eff SCv Effective Rate of

1 Effective Workstation Rate (jobs/hr)
Welding 5 0 6 0.1 8 9 10 0.0

3 0.01 4 0.

1

7 99.6% 0.02 0.33 0.0

23 0.34 0.29 0.023

64 0.28 0.30 3.38 16
Hydro 0.019 96% 25 0.

15 40 0.17 0.00 2.

49 0.0010 2.75 0.05 0.00462 1.92 1.88 19.59
Sensoring 0.025 0.006 95% 20 0.06 0.0002 0.25 0.0001 37.93
0.31 100% 9,999,999 0.07 0.04 0.5 98% 0.08 0.8 0.32 0.09 0.96 0.39 0.09867 0.65 0.10 2.56
0.23 0.53 0.0668 0.40 0.06850 0.42 2.

48
0.24 0.37 18 0.14 2.32 0.15 2.47 0.15517 1.58 0.16 3.19
4.

41 0.1084 4.65 0.20 0.10909 2.60 0.11 4.88
0.18 0.92 0.0365 1.

12 0.03755 0.62 4.06
Config 85% 6.7 0.00019 28.86
Test 0.00015 42.87
Inspection 0.015 9999999 100.0% 0.0000 0.00004 66.01
Packing 1,000,000.0 66.67
Figure 7: The Vortex Flow Lab

Product
Line Scale Avg. Weekly Demand (units) Std Dev of Demand (units) Var. of Demand (units2) Long Run Avg. Mix Process Time (min.) Setup Time (min.) Run Time per Week (min.) Total Time per Scale (min.) Process Time (hrs) Set up (hrs)
6.668 380.08 2070.41
70.014 1470.29
106.69
13 113.36 0.

22
35 286.72 2690.

54 0.58 0.13
16.67 43 833.50 0.72 0.12
10.002 290.06
80.016 1280.26
1000.20 498

1.00 0.90
783.49 0.68
116.69 1516.97
120.024 1680.34
460.09 2817.23 0.67
123.358 1356.94
100.02
1210.24 0.38
466.76
56.678 453.42
Totals 790.16 19.18 13769.42

Functions

Name Description Parameters
BreakVar Formula for breakdown variability BreakVar(NatVar, A, MTTR, MTTR-VAR,T-O)
NonPreVare Formula for set-up or recycle NonPreVar(NatVar, StdDevSU, N, SUTime)

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