Application Of Service Composition Technology Based On Petri Net In Cloud Manufacturing Platform

As a manufacturing power,China has the richest manufacturing resources in the world and a large number of manufacturing companies.At the present stage,most manufacturing companies are still using traditional manufacturing methods,resulting in a large number of idle manufacturing resources that cannot be effectively used.There is an urgent need for a more efficient manufacturing model to improve the utilization of manufacturing resources to adapt to changes in demand.In order to solve the problem that the utilization rate of idle resources in the current manufacturing industry cannot be effectively improved,this paper proposes a service composition process model to realize the automatic composition of services and applies this model to the cloud manufacturing platform to enable different regions and different scales Idle manufacturing resources in a manufacturing enterprise can participate in a certain manufacturing task.The most critical issue in this model is how to perform service optimization and how to improve the efficiency of service portfolio execution.Aiming at the problem of service optimization,this paper proposes a multi-layer QoS(Quality of Service,QoS)service model based on functional grouping and conducts simulation experiments on this model.The experimental results show that the comprehensive QoS attribute value calculated by the model is not only higher than the random service selection method,but also the calculation result gradually tends to a stable state as the number of service requests increases.This model first divides the candidate services into multiple service groups based on function,divides the QoS attributes of the services in the group into two levels: performance layer and credit layer,and then standardizes the QoS attribute values ??and assigns weights to users.Finally,a comprehensive evaluation of QoS is performed,and the services in the group are filtered again according to the results of the QoS evaluation,which improves the matching efficiency of services.Aiming at the problem of service composition execution efficiency,this paper uses the knowledge of fuzzy time-series Petri nets to propose a service dependency graph generation algorithm based on FTPN and IOPE,and combines ontology knowledge to construct service examples,and uses the improved forward and reverse reasoning algorithm to service dependency graph.By removing redundant services,a lightweight service dependency sub-graph that meets the needs of users is finally obtained,and the corresponding service composition process in the graph is returned to the users to complete a certain manufacturing task they need.