With the advances in the information and computing technologies, the ways the manufacturing enterprise systems are being managed are changing. More integration and adoption of the system perspective push further towards a more flattened enterprise. This, in addition to the varying levels of aggregation and details and the presence of the continuous and discrete types of behavior, created serious challenges for the use of the existing simulation tools for simulating the modern manufacturing enterprise system. The commonly used discrete event simulation (DES) techniques face difficulties in modeling such integrated systems due to increased model complexity, the lack of data at the aggregate management levels, and the unsuitability of DES to model the financial sectors of the enterprise. System dynamics (SD) has been effective in providing the needs of top management levels but unsuccessful in offering the needed granularity at the detailed operational levels of the manufacturing system. On the other hand the existing hybrid continuous-discrete tools are based on certain assumptions that do not fit the requirements of the common decision making situations in the business systems. This research has identified a need for new simulation modeling approaches that responds to the changing business environments towards more integration and flattened enterprise systems. These tools should be able to develop comprehensive models that are inexpensive, scalable, and able to accommodate the continuous and discrete modes of behavior, the stochastic and deterministic natures of the various business units, and the detail complexity and dynamic complexity perspectives in decision making. The research proposes and develops a framework to combine and synchronize the SD and DES simulation paradigms to simulate the manufacturing enterprise system. The new approach can respond to the identified requirements in simulating the modern manufacturing enterprise systems. It is directed toward building comprehensive simulation models that can accommodate all management levels while explicitly recognizing the differences between them in terms of scope and frequency of decision making as well as the levels of details preferred and used at each level. This SDDES framework maintains the integrity of the two simulation paradigms and can use existing/legacy simulation models without requiring learning new simulation or computer programming skills. The new framework uses a modular structure by which the SD and DES models are treated as members of a comprehensive simulation. A new synchronization mechanism that that maintains the integrity of the two simulation paradigms and is not event-driven is utilized to coordinate the interactions between the simulation modules. It avoids having one simulation paradigm dominating the other. For communication and model management purposes the SDDES formalism provides a generic format to describe, specify, and document the simulation modules and the information sharing processes. The SDDES controller which is the communication manager, implements the synchronization mechanism and manages the simulation run ensuring correct exchange of data in terms of timeliness and format, between the modules. It also offers the user interface through which users interact with the simulation modules.