Simplifying the verification of simulation models through Petri net to FlexSim mapping

Simplifying the encoding of a simulation conceptual model representation reduces the number of errors that will be detected in the verification phase. In this paper, we present a mapping between Petri nets, a well-known formalism, and FlexSim, a well-known simulation tool. The proposal is illustrated through an example of how a model specified in a Petri net can be encoded easily, reducing the time needed to understand and verify the model. In the proposed methodology, the mapping must be defined at the initial stage of the encoding, starting from (in this case) a Petri net conceptual model, and ending at the encoding tool (FlexSim in this case). The main advantages of the proposed methodology are discussed.Peer ReviewedPostprint (author's final draft

Study for the design of a management system for AGV networks

Automated Guided Vehicles are a vital part of the future intelligent manufacturing processes. In order to make the better profit, it is important to study if deadlocks can occur and how to tackle them. In this project we demonstrate how Petri Net models, which are perfect for representing deadlocks, can be mapped in the simulation software FlexSim. Eventually, we are using this software in order to evaluate different study cases with deadlocks

A conceptual modeling technique for discrete event simulation of operational processes

A formal modeling technique, based on colored timed Petri net and UML static structure modeling languages is used to teach students to model their business process problem as a discrete event system, before they build a working simulation model in a simulation tool (in our case Arena). Combining Petri net and UML static structure diagrams, one can build an abstract, well defined and complete model. This model enables the simulation analyst to make an unambiguous, complete and yet easily readable model of the target operational process. The two most important classes of decisions that are reflected in the conceptual model are the choice of the real world details to be taken in or left out the model and the precise specification of the output parameters of the simulation. This paper describes the modeling technique and discusses its value in teaching and in the formulation of decision problems regarding operational processes

A conceptual modeling technique for discrete event simulation of operational processes

A formal modeling technique, based on colored timed Petri net and UML static structure modeling languages is used to teach students to model their business process problem as a discrete event system, before they build a working simulation model in a simulation tool (in our case Arena). Combining Petri net and UML static structure diagrams, one can build an abstract, well defined and complete model. This model enables the simulation analyst to make an unambiguous, complete and yet easily readable model of the target operational process. The two most important classes of decisions that are reflected in the conceptual model are the choice of the real world details to be taken in or left out the model and the precise specification of the output parameters of the simulation. This paper describes the modeling technique and discusses its value in teaching and in the formulation of decision problems regarding operational processes

A conceptual modeling technique for discrete event simulation of operational processes

A formal modeling technique, based on colored timed Petri net and UML static structure modeling languages is used to teach students to model their business process problem as a discrete event system, before they build a working simulation model in a simulation tool (in our case Arena). Combining Petri net and UML static structure diagrams, one can build an abstract, well defined and complete model. This model enables the simulation analyst to make an unambiguous, complete and yet easily readable model of the target operational process. The two most important classes of decisions that are reflected in the conceptual model are the choice of the real world details to be taken in or left out the model and the precise specification of the output parameters of the simulation. This paper describes the modeling technique and discusses its value in teaching and in the formulation of decision problems regarding operational processes