Compressed limit sampling inspection plans for food safety

The design of attribute sampling inspection plans based on compressed or narrow limits for food safety applications is covered. Artificially compressed limits allow a significant reduction in the number of analytical tests to be carried out while maintaining the risks at predefined levels. The design of optimal sampling plans is discussed for two given points on the operating characteristic curve and especially for the zero acceptance number case. Compressed limit plans matching the attribute plans of the International Commission on Microbiological Specifications for Foods are also given. The case of unknown batch standard deviation is also discussed. Three-class attribute plans with optimal positions for given microbiological limit M and good manufacturing practices limit m are derived. The proposed plans are illustrated through examples. R software codes to obtain sampling plans are also given. Copyright © 2016 John Wiley & Sons, Ltd.

[1]  Susanne Dahms.  Microbiological sampling plans - Statistical aspects* , 2004 .

[2]  D. Sommers,et al.  Two-Point Optimal Narrow Limit Plans with Applications to MIL-STD-105D , 1981 .

[3]  A. C. Baird‐Parker,et al.  A system for setting numerical microbiological specifications for foods. , 1979, The Journal of applied bacteriology.

[4]  William C. Guenther,et al.  Use of the Binomial, Hypergeometric and Poisson Tables to Obtain Sampling Plans , 1969 .

[5]  P. Newcombe,et al.  A three-class procedure for acceptance sampling by variables , 1988 .

[6]  Dean V. Neubauer,et al.  Acceptance Sampling in Quality Control, Second Edition , 2009 .

[7]  K. Govindaraju,et al.  A combined attributes-variables plan , 2015 .

[8]  Basil Jarvis,et al.  Statistical Aspects of the Microbiological Examination of Foods , 2008 .

[9]  N. L. Johnson,et al.  Discrete Multivariate Distributions , 1998 .

[10]  I. Olkin,et al.  Can data recognize its parent distribution , 1999 .

[11]  Yalin Chen,et al.  Multilevel Fixed and Sequential Acceptance Sampling: The R Package MFSAS , 2011 .

[12]  M. W. Reij,et al.  Modelling homogeneous and heterogeneous microbial contaminations in a powdered food product. , 2012, International journal of food microbiology.

[13]  Shaul P. Ladany,et al.  Efficient Sampling by Artificial Attributes , 1974 .

[14]  M. Zwietering,et al.  Impact of microbial distributions on food safety I. Factors influencing microbial distributions and modelling aspects , 2012 .

[15]  Andreas Kiermeier,et al.  Visualizing and Assessing Acceptance Sampling Plans: The R Package AcceptanceSampling , 2008 .

[16]  S. Malcolm.  A note on the use of the non-central t-distribution in setting numerical microbiological specifications for foods. , 1984, The Journal of applied bacteriology.

[17]  V. Scott,et al.  Listeria monocytogenes: low levels equal low risk. , 2003, Journal of food protection.

[18]  J. Horowitz,et al.  Estimating the frequency of high microbial counts in commercial food products using various distribution functions. , 2001, Journal of food protection.

[19]  Shaul P. Ladany.  Determination of Optimal Compressed Limit Gaging Sampling Plans , 1976 .

[20]  Martin B. Cole,et al.  Determining the concentration of microorganisms controlled by attributes sampling plans , 2001 .

[21]  S Dahms,et al.  Some remarks on the design of three-class sampling plans. , 1998, Journal of food protection.

[22]  Irving W. Burr,et al.  Three Class Attributes Plans in Acceptance Sampling , 1973 .