Question re Zscore to Estimate Quantity of Defective Units
Six Sigma – iSixSigma › Forums › General Forums › Tools & Templates › Question re Zscore to Estimate Quantity of Defective Units
 This topic has 3 replies, 1 voice, and was last updated 11 months, 2 weeks ago by VazBelt.

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July 12, 2019 at 10:20 am #240402
DdelisleParticipant@Ddelisle Include @Ddelisle in your post and this person will
be notified via email.I sent this discussion earlier today but cannot find it on the forum… not sure what happened.
Using this partial Z Table, how many units from a month’s production run are expected to not satisfy customer requirements for the following process?
Upper specification limit: 8.4 Lower specification limit: 4.7 Mean of the process: 6.2 Standard Deviation: 2.2 Monthly production: 360 units
Please choose the correct answer.Response: 57 (from test service)
I approached this question by looking the zscore for upper and lower limits and adding the two to get the total estimate.
My calc:
UCL: (8.46.2)/2.2 = 1.00 (zscore). I change the sign (1.00) to get the area to the left and come up with .1587 .1587*360=57
LCL
UCL: (4.76.2)/2.2 = .68 (zscore). Zscore = .2483*360=89.4
Add the 89+57 = 146 for a total estimated defects. I know that this answer does not make sense since we are within one std on upper side and more than one on lower side. So defects would be less than 115 (1.68)*360.
So where am I going wrong?
Thanks
0July 12, 2019 at 11:07 am #240404
Chris SeiderParticipant@cseider Include @cseider in your post and this person will
be notified via email.Another bad test example?
Your total bad looks fine assuming the Z scores are correct.
I don’t understand your last paragraph. You have more defective on the lower side than on the upper side so you’d expect to have more than the normal distribution of 31.7% defective since you produce a higher defect rate on the lower side. Draw the normal curve, place the specs and darken the defective areas. Then do the same for dark areas for +/ 1 s.d. out of spec–which has more.
0July 13, 2019 at 7:53 am #240433
DdelisleParticipant@Ddelisle Include @Ddelisle in your post and this person will
be notified via email.Hi Chris
In regards to the last paragraph…looking at this again, I was wrong the LCL is less than 1 sigma which would yield a higher defect rate. So my calculation of 146 still hold true. Assuming the Zscore I picked up the correct rates on the Zscore table, then I my answer should be correct… ?
Tks
Derek
0August 25, 2021 at 8:45 pm #255102
VazBeltParticipant@VazBelt Include @VazBelt in your post and this person will
be notified via email.Hi @Ddelisle
I was struggling with the same question when I came across this topic. I though it’s best to share my findings.
1. Z (ucl) = 1 > Area to the left of UCL = 0.8413 (from table)
2. Since we want the area to the right of UCL (upper rejection zone) : 1 – 0.8413 = 0.1586 — A
3. Z (lcl) = 0.6818 > Area to the left of LCL = 0.2483 (from table) — B
4. So the rejection areas = 0.1586 + 0.2483 = 0.407 — A + B
5. This means that 40.7% of the production run are expected to not satisfy customer = 40.7% of 360 units = 146
This matches your answer.I think this is the correct answer as the LCL is much stringent than 1 standard deviation, so its bound to have a higher defect than (100 – 68.26) = 31.74%; which is 40.7% in this case.
Hope this helps. :)
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