Recent research has increasingly focused on integrated statistical process control (SPC) and maintenance strategies in production systems, highlighting their critical role in quality control. Most integrated modeling of SPC and maintenance currently focus on large-scale production processes. However, production processes are transitioning towards multi-variety and small-batch production mode, which is characterized by insufficient sample sizes. Based on this characteristic, this paper studies the integrated modeling and optimization of Variable Sample Size (VSS) control chart and maintenance. This strategy employs an equal interval maintenance strategy. Within the preventive maintenance cycle, the sampling starts with a small sample size, and when the sampled result falls in the warning zone, the sample size is increased. Also, five maintenance scenarios are defined based on three maintenance types, the state of the process and whether the control chart triggers an alarm. The probabilities, costs, and durations for each scenario are also calculated accordingly. The integrated model then is established based on these scenarios, and genetic algorithms are used for case analysis to solve the optimal objective of the model. Based on the case analysis, it is demonstrated that the proposed integrated model can make effective decisions under various scenarios, thereby validating its applicability and effectiveness in small-batch production processes.