A Comparative Study of Models for Acceptance Sampling with Attribute-Variable Quality Characteristics

Document Type : Research Paper

Authors

1 M.Sc. Student, Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran

2 Associate Professor, Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran

3 Assistant Professor, Department of Engineering Sciences, Faculty of Advanced Technologies, University of Mohaghegh Ardabili, Ardabil, Iran

10.22084/ier.2025.30558.2196

Abstract

This study designs a mixed attribute-variable acceptance sampling plan (AVASP) based on process capability index. The initial design aims to minimize the cost function subjected to some statistical criteria. Then, to reduce the risks, the minimum angle method (MAM) is used to develop the bi-objective Cost-MAM model. In addition, two similar models are developed without considering economic indicator. the first model uses average sample number (ASN) as the objective function, while the second one is a bi-objective model with the ASN-MAM objective function. In order to provide appropriate results in a reasonable time, the particle swarm optimization (PSO) algorithm is used to solve the aforementioned models. The four proposed models are compared by conducting simulation studies. After selecting the preferred model, the optimal policy of the AVASP is implemented in a case study. Finally, a sensitivity analysis is presented to identify the parameters affecting the results.

Keywords

Main Subjects


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