91 TAS Journal, vol. 4, n. 2, p. 91-98. ISSN: 2595-1521 JUNE 2020 mazzoni486@gmail.com Flexible Productive Systems Modeling and Control Tools: Literature Review Mazzoni URC*, Asato OL* and Nakamoto FY* * Federal Institute of Education, Science and Technology of São Paulo - Campus São Paulo, São Paulo. Abstract. The challenges imposed on Manufacturing Systems (MS), given the demands of a dynamic and competitive market, instigates the development of new technologies to promote the reduction of production costs, increase productivity and ensure the level of quality established by the company. Such technologies applied in MS create demands for new paradigms for the design of control systems, mainly about the integration of automated systems, such as multifunction machines, flexible machining centers, intelligent robotic conveyor systems, and the integration of information systems, production planning and management, and manufacturing execution. The main purpose of control system modeling is to represent a real system using conceptual models to visualize, predict and simulate the desired dynamic behavior of the system. This article presents some modeling tools for control systems capable of adequately representing a manufacturing system with all its requirements and intrinsic characteristics, supported by formal methods for structured modeling of the control system. Keywords. Modeling Tools, Productive System Modeling, Petri Nets, E-MFG. Introduction. The globalization of the market has imposed a particular and previously non- existent dynamics on MS, which the flexibility of production processes is highly required, with demands for products and services with a gradual reduction of the life cycle, which the rational use of resources is necessary due to the sustainability of industrial processes, quality assurance and reliability as a market differential, a growing volume of data at all levels of the productive system with considerable autonomy of components and equipment. This way, it is necessary to develop new structured models to guarantee the dynamic behavior desirable to the system and effective integration of the automated systems. With the emergence of new technologies and the inherent modernization of industrial parks, it is necessary to develop new models and methodologies to adapt and ensure that the manufacturing system works effectively to produce efficiently. The modeling of the manufacturing control system has been widely studied (1, 2, 3, 5, 6, 7, 19, 20, 21) and aims to represent a real system using conceptual models for visualize, predict and simulate the desired dynamic behavior of the system. The formalism is a factor of extreme importance in the modeling of control system. Overall, formalizing can be defined by describing a process, object, phenomenon, etc., so that anyone can interpret without duality or ambiguity. Formalism ensures a correct interaction of process participants, data consistency, and a more secure process (3). Thus, the main motivation for the research work is the need to adequately represent a manufacturing system with all its intrinsic requirements and