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Changes in equipment and production demand cannot be predicted at the design stage. Therefore, decision taking mechanisms must rely on real time information collected from the shop floor. To perform scheduling and routing optimization, not only modifications in values of parameters of interest, but also in the flow itself must be accounted for. This paper addresses this problem and proposes a method to formally model, at runtime, the flow within a service-oriented manufacturing line. The resulting representation assists deadlock-free dynamic scheduling of the system.

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