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# Euro Watch Case Study

Submitted By skhazaei
Words 1076
Pages 5
Euro Watch Company Report
1 ) The Euro Watch Company assembles expensive wristwatches and then sells them to retailers throughout Europe. The watches are assembled with two assembly lines with below specification:
Line 1:
Old equipment
Less reliable
Defect rate of 2%
Capacity: 500 watches per hour
Line 2:
New equipment
More reliable
Defect rate of 1%
Capacity: 500 watches per hour
We need to find the smallest number of defected watches each line produces independently in a given hour with success rate of 99%
The distribution is a binomial distribution since we have 500 independent and identical trials with a certain probability of success and we see a defected or non- defected option therefore in the excel file we should use the command BINOMDIST. Number of trials is 500 and for cumulative we should consider 1 as we want to have the probability of less than or equal to K defects.
As we can see in below tables the smallest defected number that reaches the rate of 99% is 18 watches for line 1 and 11 defected for line 2, which is obvious since line 2 is newer, and with lower defect rate.
￼￼￼line 2 99% 1% 500
Line 2
Line ￼ line 1
￼Defect-free 98%
￼Defective 2%
￼Made watches per hour 500
￼￼Defected amount (k) Line 1 Defected amount (k)
0 0.0000
1 0.0005
2 0.0026
3 0.0098
4 0.0281
5 0.0652
6 0.1276
7 0.2175
8 0.3305
9 0.4567
10 0.5830
11 0.6979
12 0.7935
13 0.8667
14 0.9186
15 0.9530
16 0.9743
17 0.9866
18 0.9934
19 0.9969
20 0.9986
21 0.9994
22 0.9998
23 0.9999
24 1.0000
25 1.0000
26 1.0000
27 1.0000
28 1.0000
29 1.0000
30 1.0000
0
1
2
3
4
5
6
7
8
9
10
11 ￼ 0.9948
12
13
14
15
16
17
18
19
20
0.9981 0.9994 0.9998 0.9999 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000
0.0066 0.0398 0.1234 0.2636 0.4396 0.6160 0.7629 0.8677 0.9329 0.9689 0.9868…...

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