The aim of this study is to develop two repetitive types of sampling plans for processes with multiple quality characteristics on the basis of the overall yield index STpk. These plans could be implemented for mutually independent and normally distributed characteristics. The plans are optimally designed based on the asymptotic sampling distribution of STpk using an efficient nonlinear optimization algorithm. During the process of solving optimization problems, the average sample number required for inspection and contract’s requirements are considered as objective function and constraints, respectively. The optimal parameters are prepared to use in industrial environments for various combinations of requirements in some tables. A simulation study is also conducted to show that the tabulated parameters, which are found under the results of large sample theory, can properly guarantee the specified risks for finite sample sizes. Moreover, the limitation of the introduced plans regarding the sample size is analyzed based on extensive simulations. Some numerical calculations and graphical illustrations are presented to demonstrate the properties of the proposed plans. In addition, the advantages of the suggested schemes are discussed over the existing plans. Finally, the efficient plan is applied on two real industrial problems.

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