Defects in the automatic fiber placement (AFP) directly affect the prepreg bonding strength, resulting in a less strong product than expected. Improper process parameter selection is one of the major factors contributing to layup defects. However, there is a significant degree of uncertainty associated with the parameters that affect the lay-up quality and currently few studies that use response surfaces to consider the interaction of these parameters. In general, it is necessary to obtain a more accurate combination of process parameters through experiment, which is time-consuming and consumable. Moreover, it is difficult to investigate the interrelation between process parameters. Therefore, this paper presents a method of placement parameter optimization based on lap shear strength (LSS) to achieve high-quality and high-strength AFP process control. Firstly, this article establishes a comprehensive quality evaluation system by analyzing the causes of defects in AFP process. Secondly, the central composite design of experiments (CCD) response surface methodology was used to effectively optimize the process parameters and to understand the interactions between the various factors. A prediction model with quadratic polynomial regression equations for four process parameters and laydown quality was developed. Based on the regression equations, the process parameters with optimal lay-up quality were obtained. Then, using 30 sets of process parameters from the response surface experiment, lap samples were made for tensile testing. The lap shear strength of tows under various process conditions was studied, and the experimental results were consistent with the response surface analysis results. Finally, by analyzing the quality evaluation curve and load-time curve, it was found that the trend of AFP quality evaluation score and LSS was practically the same. Data analysis shows that placement using optimized parameters corresponding to higher scoring samples has higher lap shear strength and fewer defects than placement of samples with low quality scores. Therefore, the quality evaluation system of lay-up quality proposed in this paper is an effective and reliable method for optimizing the parameters of AFP process.