Euro Watch Case Study Essay

1080 Words Jun 19th, 2014 5 Pages
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
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To find the number of defect-free watches we use the function 1-BINOMDIST with trial number of 500 probabilities of 99% and cumulative to be 1 therefore we find out that we need to send minimum 511 watches, as below table shows.
line  line 2
defect-free 99%
defective 1%
made watches per hour 500
packed >=500 okay
500 0.0066
501 0.0394
502 0.1217
503 0.2594
504 0.4326
505 0.6071
506 0.7541
507 0.8603
508 0.9276
509 0.9656
510 0.9849
511 0.9939
512 0.9977
513 0.9992
514 0.9997
515 0.9999
516 1.0000
517 1.0000
518 1.0000
519 1.0000
520 1.0000

3) There is an order of 1000 watches to produced with the same number of watches from each line, we need to calculate the number of watches to be sent, so that the customer receives at least 1000 defect free watches.
We try to find out the number of watches with defect, first we calculate number of defected watches randomly for each line separately then we add this number to calculate the total defect in each trial to calculate the total defect free watches.
Later on we calculate the average probability of having at least 1000 defect-free watches, we start as a trial with 508 watches for each line and we find out the average pr is 65.88% we continue to add more production to reach the 99%, as we can see in below table the production number of 512, 513 have an average more than 99%, so the suggested number to

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