hi..
ive got problem in developing the OC curve
right now i have 6 months data with various number of batches and sample sizes..i substitute all the data so then it given all the number of total incoming,total sample size and total reject

for example:

MONTH 1
Total Incoming : 7000
Total Sample Size : 500
Total Reject : 99
Target: 100%
OK : 98.59%
Reject : 1.41%

ive also develop percentage graph for that data..so is that possible to develop OC curve from the data that i got?or ive to calculate every batches which means ive to develop alot of OC curves for 6 months?how??

i really need help for this.
thanks.

Welcome to the Cove.

Pending further response from our fellow Covers, you may want to do a search on previous discussions on this same subject. Who knows, you may find your answers there. This is a typical google search result (http://www.google.com/custom?domains=Elsmar.com&q=develop+oc+curve&sitesearch=Elsmar.com&client=pub-1385417534940691&forid=1&channel=6124086287&ie=ISO-8859-1&oe=ISO-8859-1&cof=GALT%3A%23008000%3BGL%3A1%3BDIV%3A%23336699%3BVLC%3A663399%3BAH%3Acenter%3BBGC%3AFFFFFF%3BLBGC%3A000099%3BALC%3A000000%3BLC%3A000000%3BT%3A0000FF%3BGFNT%3A0000FF%3BGIMP%3A0000FF%3BLH%3A50%3BLW%3A350%3BL%3Ahttp%3A%2F%2Felsmar.com%2Fpng%2Fheader-G-search.png%3BS%3Ahttp%3A%2F%2FElsmar.com%2FForums%2F%3BFORID%3A1%3B&hl=en).

what exactly are you trying to do?
and what is your sample plan? how many parts inspected and how many rejects required to reject the lot? do you 100% inspect the lot after inspection? how many parts are found during 100% inspection and how many found during the sample inspection....

OC curves are not generated from actual data. they are generated from the sample size and reject on number vs various possible defect rates.

I would suggest that you search this site and others for OC curve and AOQ curve and then come back with specific clarifying questions.

Welcome to The Cove!

Is this a class assignment?

Based on the information provided, I was not able to give an answer to this question. But I have received some more information in a message:
hi there^^
thanks for your concern
actually it is not a class assignment..
it is more to case study since the data that ive used were came from one of company here..uh~how do i say?a thesis??

after searching and reading alot of sampling plan info...correct me if im wrong
-sample size = n
-lot size = N
-acceptance number = c
-true lot fraction defective = p

but im still confused on how to determine c and p..

if ive N=1000,n=20
and from the company table,for n = 20,
-if one defect found = accept
-if 2 and more defect found = reject
so how to determine p?from p,then i can get Pa and draw the OC curve right?

another question,
since for 1 month (example;January) the company have a lot of incoming for this part(eg;XX),if that any possibilities that i can combine all the curves in one graph paper?

im really confused with this matter.
thanks for your concern..

If you are referring to "Operating Characteristic Curves", these are determined from the parameters of the test you use, not from the data.

What an OC Curve represents is - if the "true" value of the characteristic being measured were a certain quantity, what would be the percent chance of the test rejecting a sample from that population. Thus you can assess the probability of a "false alarm" with a relatively good population, and the probability of a "failure to detect" from a relatively bad population.

If you are referring to "Operating Characteristic Curves", these are determined from the parameters of the test you use, not from the data.

What an OC Curve represents is - if the "true" value of the characteristic being measured were a certain quantity, what would be the percent chance of the test rejecting a sample from that population. Thus you can assess the probability of a "false alarm" with a relatively good population, and the probability of a "failure to detect" from a relatively bad population.

thanks for your concern..
yes,AQL that im concerned is 'Operating Characteristic Curve'..
can you tell me more in d most simple way so that i can fully understand?
im still new in sampling plan and AQL..and more of d info in internet not showing the basic explanation for me.

Here are 2 quick searches which might help:

OC (Operating Characteristics) Curves (http://www.google.com/custom?domains=Elsmar.com&q=oc+curve&sa=Search&sitesearch=Elsmar.com&client=pub-1385417534940691&forid=1&channel=6124086287&ie=ISO-8859-1&oe=ISO-8859-1&cof=GALT%3A%23008000%3BGL%3A1%3BDIV%3A%23336699%3BVLC%3A663399%3BAH%3Acenter%3BBGC%3AFFFFFF%3BLBGC%3A000099%3BALC%3A000000%3BLC%3A000000%3BT%3A0000FF%3BGFNT%3A0000FF%3BGIMP%3A0000FF%3BLH%3A50%3BLW%3A350%3BL%3Ahttp%3A%2F%2Felsmar.com%2Fpng%2Fheader-G-search.png%3BS%3Ahttp%3A%2F%2FElsmar.com%2FForums%2F%3BFORID%3A1%3B&hl=en)

Using OC Curves (http://www.google.com/custom?hl=en&client=pub-1385417534940691&channel=6124086287&cof=FORID%3A1%3BGL%3A1%3BS%3Ahttp%3A%2F%2FElsmar.com%2FForums%2F%3BL%3Ahttp%3A%2F%2Felsmar.com%2Fpng%2Fheader-G-search.png%3BLH%3A50%3BLW%3A350%3BLBGC%3A000099%3BT%3A%230000ff%3BLC%3A%23000000%3BVLC%3A%23663399%3BDIV%3A%23336699%3B&domains=Elsmar.com&ie=ISO-8859-1&oe=ISO-8859-1&q=oc+curve&btnG=Search&sitesearch=)

The OC curve has the probability of accepting the lot on the y-axis and the actual proportion defective on the x-axis (1% defective would be 0.01). This Excel formula will generate the probability of acceptance: BINOMDIST(c, n, p, TRUE) where c = accept number, n = sample size, p = actual proportion defective, and TRUE is a cumulative flag. To draw an OC curve (or even to look one up in a book of curves), you need to know c and n. Put values from 0 to 1 in a column to use as p, and put the formula in a second column. Have Excel draw a curve with p as the x-axis and the formula results as the y-axis.

The OC curve has the probability of accepting the lot on the y-axis and the actual proportion defective on the x-axis (1% defective would be 0.01). This Excel formula will generate the probability of acceptance: BINOMDIST(c, n, p, TRUE) where c = accept number, n = sample size, p = actual proportion defective, and TRUE is a cumulative flag. To draw an OC curve (or even to look one up in a book of curves), you need to know c and n. Put values from 0 to 1 in a column to use as p, and put the formula in a second column. Have Excel draw a curve with p as the x-axis and the formula results as the y-axis.
thanks alot^^
is that c is how many accept parts within the sample size inspect?
if we have N=1000,n=20,and we reject if found 3 defects..so c = 17?

No. C is the number of nonconforming parts allowed in the sample.

Many sampling plans used today are C = 0 plans, which means the lot is rejected if one nonconforming part is found in the sample.

^
thanks for helpin
and sorry because asking too much questions here..

d company that ive done this case study run d inspection process using table in the attachment..
for example,
for sample size of 20, there are two possibilities in accepting the lot,either 0 or 1..so ive need to calculate both p and then add it?

for info,im investigating the inspection process before and after implementing AQL.And the result after implementing AQL was it causes a drastic changed in terms of cost and quantity of reject.Actually my target was achieved based on that result but then my lecturer want me to draw OC Curve just because sampling plan must have OC Curve.


(already lost a lot of energy because of this sampling plan:()

Your sampling plan actually looks like a plan straight out of the standard ASQ Z1.4 sampling plans - I'll leave it to you to figure out which plan.

You can look up the tables in the old MIL-STD-105E (equivalent to Z1.4) found here.
http://assist.daps.dla.mil/quicksearch/basic_profile.cfm?ident_number=35496

Once you have figured out how to do the OC curve from the friendly advice you have already received, you can actually check your results since the tables list the OC curves!

Tim F

Hi Irzs_2ue,

Enclosed herewitha excel file for calculate OC curve using single sampling, just change the sampling size, n and acceptable number, c and number of column to your need.


Rgrds
meimei

Hi Irzs_2ue,

Enclosed herewitha excel file for calculate OC curve using single sampling, just change the sampling size, n and acceptable number, c and number of column to your need.


Rgrds
meimeiI like it! :applause: I have renamed the file so it is easy to find when searching the Post Attachments List function.

Hi Irzs_2ue,

Enclosed herewitha excel file for calculate OC curve using single sampling, just change the sampling size, n and acceptable number, c and number of column to your need.


Rgrds
meimei

That is a handy spreadsheet.

It looks like you are assuming a Poisson distribution (i.e. it is possible to have more than one defect per item). The results will be slightly different for people who have a binomial distribution (i.e. each item is either defective or not).

Meimei, you might try using the BINOMDIST and POISSON functions in Excel. It should allow you to streamline the spreadsheet a little. For instance, the spreadsheet could handle various c values without having to manually change the number of columns if you use the "cumulative" option within these Excel functions.

Tim F