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A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer’s risk and consumer’s risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.

The integrated automation system consisting of production process management system, optimal system of production indices and process control system is established for the optimization of production indices of minerals processing. The structure and functions of this system are discussed. The optimal control strategy for production indices is proposed to transform the target of production indices into the optimal setpoints of process control system automatically. It has been applied successfully to the largest hematite minerals processing factory of China with significantly proven benefits. Industrial applications show the good performance of the suggested system and its bright future in the industry.

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Acceptance sampling plans are useful tools to determine whether the submitted lots should be accepted or rejected. An efficient and economic sampling plan is very desirable for the high quality levels required by the production processes. The process capability indexCLis an important quality parameter to measure the product quality. Utilizing the relationship between theCLindex and the nonconforming rate, a repetitive group sampling (RGS) plan based onCLindex is developed in this paper when the quality characteristic follows the Weibull distribution. The optimal plan parameters of the proposed RGS plan are determined by satisfying the commonly used producer’s risk and consumer’s risk at the same time by minimizing the average sample number (ASN) and then tabulated for different combinations of acceptance quality level (AQL) and limiting quality level (LQL). The results show that the proposed plan has better performance than the single sampling plan in terms of ASN. Finally, the proposed RGS plan is illustrated with an industrial example.

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