Control charts are a basic means for monitoring the quality characteristics of processes to ensure the required quality level. Determine the sample size is a problem for attribute control charts (ACC). Kaya and Engin [I. Kaya, O. Engin, A new approach to define sample size at attributes control chart in multistage processes: an application in engine piston manufacturing process, J. Mater. Process. Technol. 183 (2007) 38-48] developed a model to determine sample size in multistage process and it was solved by Genetic Algorithms (GAs). In their model, the parameters such as defective item rates for raw materials and benches were assumed to be known exactly. But in many real world applications, these parameters may be changed very dynamically due to material, human factors or operating faults. In this study a fuzzy approach for ACC in multistage process is presented and it is solved by GAs. Formulations of this model are calculated based on acceptance sampling approach and, two main parameters are determined for every stage by GAs. These are: sample size, n, and acceptance number, c. The sample size, n, is suggested for ACC. The main contributions of this paper are to develop a fuzzy model for ACC in multistage processes. The proposed approach is applied in an engine valve manufacturing firm and the model is solved by GAs. (c) 2008 Elsevier B.V. All rights reserved.