Specifying Efficient Design Parameters of Single Sample Acceptance Sampling Plans

In quality assurance systems, acceptance sampling (AS) plans, as one of the main fields of statistical quality control, play a very important role. The design of a single AS plan generally requires determination of sample size, and acceptance number. Several models for optimally selection of design parameters have been developed in the literature including a variety of approaches. In this study, it is intended to reach a well-balanced compromise between cost (economical) and quality (statistical) features. Thus, a multi-objective economic-statistical design (MOESD) of the single AS plan is presented. A simple and efficient optimization algorithm using data envelopment analysis (DEA) is employed to solve it. Through a simulation study, the efficiency of proposed model is illustrated. Moreover, a comparison of optimal designs obtained using economic model with statistical constraints, and the MOESD is made.