Abstract: With the increasing demand for fine chemical products in market, the proportion of batch production process in chemical production has become larger. In order to improve the economic efficiency of enterprises and ensure the safety of production, it is quite necessary to monitor and assess the control performance of batch processes. Aiming at the performance monitoring and assessment problem of batch process control system under the limited controller structure, a new control performance assessment scheme based on an improved MKPCA algorithm is proposed in this paper. Firstly, the controller parameters are optimized using the gravitation search algorithm, by which the output error data set with better control performance can be obtained. And then, several multivariate statistical process control (MSPC) methods are used to establish the principal component models for the data set, which are further used to monitor the new batch process output data. Besides, an online control charts-based integrated control performance index (CPI) is designed to assess the performance of batch process control systems. The assessment mode of proposed CPI is the same as the traditional continuous process control system assessment method such that the assessment result of the batch process control system at the current sampling time can be obtained intuitively. Finally, the simulation experiments are made to verify the accuracy of the improved MKPCA method in monitoring control performance of batch process, which shows that the improved MKPCA method can attain the best monitoring performance among four MSPC methods. Moreover, the effectiveness of the proposed integrated CPI is also demonstrated by the control charts of the improved MKPCA method.