Single sampling plans is one of the tools used in industry for accept or reject lots. Normally, the necessary parameters-producer and consumer's risk, and acceptable and limiting quality level-are assigned by either producer or consumer seeking their individual benefit. Making decisions in this way does not take into account the damage that a nonconforming product generate to the society, for example the injuries produced by a defective machine to operators. In the present study we develop a model that combines single acceptance sampling plans by attribute with the control chart for number of nonconforming products. The model maximizes social welfare by finding optimal pricing policies, sample size, and acceptance number. This methodology allows identifying unexpected changes in the production process and implementing recovery plans for customer affected by nonconforming products. Finally, our methodology also enhances the implementation of plans for continuous improvement.