On the generalization of continuous-time stochastic processes simulation for industrial production modeling

The paper presents a new generalized framework for carrying out simulations of continuous-time stochastic processes by exploiting a discrete event approach. The application scope of this work mainly refers to industrial production processes executed on a continuous flow of material (e.g., food and beverage industry) as well as production processes working on discrete units but characterized by a high production rate (e.g., automated packaging lines). The proposed model extends a previous work of the same Authors by introducing the capability to manage logical signals between couples of simulation units. In this way, control policies can be modeled and triggered by variations on parameters under monitoring during the simulation. A generalized model for a generic simulation unit is then presented and described adopting the DEVS formalism.