Modeling of Distributed Collaborative Control Systems of Production Systems

The market needs requires the Production Systems (PS) to offer a diversity of products, at shorten product life cycles, with cost and quality exigencies. It means PS have to support concurrent execution of production processes, to coordinate the shared resources according to each resource type management and operational strategies, and to deal with time varying set of processes. The control systems of PS are challenged to meet the requirements to support such time varying, concurrent, complex processes. Not only the resource flexibility, but also the flexibility resident in the control systems is now required. This work introduces a modeling technique of distributed collaborative control systems of PS (DCCS). It proposes the multifaceted decomposition in other to approach complexity of many interrelated problems of different natures. Observing the inherent distribution of information in PS, decomposition is considered at four facets: semantic, functional, temporal and spatial decomposition. The result is a collaborative hierarchies architecture, in which a heterogeneous set of control systems collaborate to the PS global objectives. It also introduces the Extended Mark Flow Graph (E-MFG) with Communicators, which can be applied to model the individual behavior of the distributed control systems. Control systems, when seen as discrete event driven systems, can be modeled by Petri nets. E-MFG is derived from Condition/Event Petri nets; it is an interpreted net, with individual marks. Communicators are new elements of E-MFG witch supports the modeling of message based communication of control systems in the distributed environment. The communication specifications, which define the collaborative behavior of the control systems, and the modeling systematic of DCCS are briefly discussed.