A tracking simulator is a decision support application in which dynamic estimation is used to continuously align the results of an online first principle simulation model with the measurements of the targeted plant. They are a holistic application where current and future plant information is available for operation support of process plants. Existing tracking simulators have focused on the application of online and offline methods for estimation of their underlying first principle models (FPMs). However, these systems have been less attractive than similar alternatives based on empirical modeling, due to the lack of systematic approaches that address challenges across the tracking simulation lifecycle, such as laborious development of FPMs and high integration costs with the process or with other systems and simulation methods. In contrast, the approach presented in this paper integrates a tracking simulation architecture and various simulation methods to address the described challenges as follows. In order to tackle time-consuming development of FPMs, a method for generating tracking simulation models from models created during design phase is proposed. The process of connecting the tracking simulator to the physical plant and initializing the tracking simulator is automated. An optimization method for tracking simulation applications is developed to overcome drawbacks of available methods. The simulation architecture developed applies the proposed methodology during the various phases of tracking simulation. Furthermore, it exploits industrial communication standards to avoid the need for point-to-point integration of various simulators and other systems used over the course of the tracking simulator lifecycle. The work is demonstrated with laboratory process equipment.