Repeated screening is a 100% sampling inspection of a batch of items followed by removal of the defective items and further iterations of inspection and removal. The reason for repeating the inspection is that the detection of a defective item happens with probability p < 1. A missed defective item is a false negative result. The no false positive result is contemplated in this paper, which is motivated by a problem coming from the production of pharmaceutical pills. Bayesian posterior distributions for the quality of the lot are obtained for the case of both p known and p unknown. Batch rejection and batch acceptance control limits for the number of defective items at subsequent iterations can then be calculated. Theoretical connections to the problem of estimating the number-of-trials parameter of a binomial distribution are drawn.
Repeated screening with inspection error and no false positive results with application to pharmaceutical pill production / Gasparini, M.; Nusser, H.; Eisele, J.. - In: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS. - ISSN 0035-9254. - 53:1(2004), pp. 51-62. [10.1111/j.1467-9876.2004.00425.x]
Repeated screening with inspection error and no false positive results with application to pharmaceutical pill production
Gasparini M.;
2004
Abstract
Repeated screening is a 100% sampling inspection of a batch of items followed by removal of the defective items and further iterations of inspection and removal. The reason for repeating the inspection is that the detection of a defective item happens with probability p < 1. A missed defective item is a false negative result. The no false positive result is contemplated in this paper, which is motivated by a problem coming from the production of pharmaceutical pills. Bayesian posterior distributions for the quality of the lot are obtained for the case of both p known and p unknown. Batch rejection and batch acceptance control limits for the number of defective items at subsequent iterations can then be calculated. Theoretical connections to the problem of estimating the number-of-trials parameter of a binomial distribution are drawn.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2883081