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Hi all, i find difficult to understand the standard sampling plan in detail, may be is because i do not have any statistic background. To make thing simple, i plan to base on historical quality data to determine the sample size.
For example we buy carton from supplier for medical device packaging, base on Jun 09 - Jun 10 data, let say the total carton loaded to production was 10,000pcs, total rejected carton segregated from production was 50pcs, means failure 0.5%. Can we treat this 0.5% as the smallest sample size that we should sample from an incoming lot in next receiving from supplier? or may be for better assurance we high up the % to 0.6% for better assurance.
If today we received a new lot from supplier with Qty 5000, sample size (0.6%) = 30pcs and C=0. Is is a acceptable method?
To be more meaningful, the supplier quality performance data will have to be reviewed by quaterly basis to minitor the supplier quality performance, at the same time adjust incoming sampling plan to change the sampling sensitivity. Base on quarterly analysis, we can also identify what are the major supplier rejection symptoms that we should focus in receiving sampling inspection. I believe we can use this method to justify why we use a specific sample size, don't you think this is more practical instead of apply complicated sampling plan like 1.9, 1.4, C=0 ?
Please advise. Thanks.
For example we buy carton from supplier for medical device packaging, base on Jun 09 - Jun 10 data, let say the total carton loaded to production was 10,000pcs, total rejected carton segregated from production was 50pcs, means failure 0.5%. Can we treat this 0.5% as the smallest sample size that we should sample from an incoming lot in next receiving from supplier? or may be for better assurance we high up the % to 0.6% for better assurance.
If today we received a new lot from supplier with Qty 5000, sample size (0.6%) = 30pcs and C=0. Is is a acceptable method?
To be more meaningful, the supplier quality performance data will have to be reviewed by quaterly basis to minitor the supplier quality performance, at the same time adjust incoming sampling plan to change the sampling sensitivity. Base on quarterly analysis, we can also identify what are the major supplier rejection symptoms that we should focus in receiving sampling inspection. I believe we can use this method to justify why we use a specific sample size, don't you think this is more practical instead of apply complicated sampling plan like 1.9, 1.4, C=0 ?
Please advise. Thanks.