Sampling plans by variables for inflated-Pareto data in the food industry

The inspection samples of raw material such as chemical substances in the food industry follow the inflated-Pareto distribution. To reduce the required sample size and maintain the same protection for producer and consumer, we propose three new variables sampling plans, including resubmitted sampling, repetitive group sampling (RGS), and multiple dependent state repetitive (MDSR) sampling plans. The MDSR plan outperforms the other three plans in terms of the sample size required. The proposed plans can reduce the sample size by 25–70% compared to the single sampling plan.

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