[Sergei]

Thank you, Darth. You are right. it’s 97 463 for 100 000.
So, the one chance to reduce the sample size is to try to use variable data. Am I right?
In this case, what should we do, if we can’t  gather continuous measure because of nature of a product (for example almost all data at food industry is attribute)?
I agree also that we have to be careful using a p-chart with proportions that small. And I have another question from that: is it effective to monitor a process by control charts if the fraction defective is very very small. The answer I think no, it’s not effective. To use charts we have to have enough defects but to get enough defects we have to check a very big sample. I can’t find the right way from that.

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[Sergei]

I got the formula from one Six Sigma book and I don’t know exactly how it works and why it is true. I just hope that it’s right formula. Anyway it helps to get smaller sample size according to someone opinion.
The formula: if m/N > 0.5 then use  n = m/(1+m/N)
‘N’ is the population size.
‘m’ is sample size not taking into consideration population size
‘n’ is the final sample size taking into consideration population size.
 

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[Sergei]

Thank you all for a replies. In fact it was teoretical question. Nevertheless we can take reasonably truthful data below.
Population size: 100 000.
Desired confidence level: 0,95
Current proportion defective: about 0,0001
Desired precision: 0,00001
I can define the sample size here and it is 3 841 070 not taking into consideration the population size and it’s 793 434 taking into consideration the population size. These numbers are too big and I know that they came from very small desired precision. At the same time I think it’s right to choose a precision level smaller than current proportion defective. So my questions are the same: What to do? Thank you.
 

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[Sergei]

It’s all about audit and consulting company. The project is about to reduce the time of arrangement of tax and business accounting at client organization.
The main CTQC’s are time of projects, a project team have to be unchanged during the project, there have to be no idle reference and other.
Unfortunately there is few data availible. Time data was recieved by internal Lotus system. The other data was recieved by questionnaires. I should notice that almost all data is approximate because each employee has a subjective opinion and approximateness is difficult to assess. Of course questionnaires was composed to guarantee consistency and accuracy.
As a result I have CTQC’s and evaluative data to each CTQC respectively. The question is the same: because of complexity can I go to the next phase (analysis) or I have to give attention to some more points?
Thanks a lot.

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[Sergei]

Thanks for reply. I learned a BB course through the internet.And now my Company tries to improve processes and smth like this by itself. I’m working in consulting and it happened that in the measure phase I just have bare figures and it’s not applicable to use tools as G&G, Pareto, Histogram and other. Is it a normal situation? Are there points that Must be achieved in any measure phase and must be included in any gate review after measure phase?
Thanks. 

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[Sergei]

Hello. It’s interesting for me. Please forward your case study to: s_baumaval.ru .  Thanks a lot!

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[Author]

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