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Design,Implementation And Intelligent Scheduling Of A Digital Twin Production Line Based On VUP And Any Logic

Posted on:2023-10-12Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZhaoFull Text:PDF
GTID:2558306908964489Subject:Engineering
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Today,a new round of scientific and technological revolution and industrial transformation is under rapid development.All major developed countries around the world embraced intelligent manufacturing and put forward corresponding industrialization strategies.Digital twin and artificial intelligence are important underpinning technologies for intelligent manufacturing.Intelligent factories/workshops/production lines are important carriers to implement intelligent manufacturing.A digital twin production line is the basic unit that integrate human,information,and physical system deeply.Analysis of digital twin production line is not only helpful to understand digital twin systems,but also beneficial to rapid practical implementation of digital twins.This thesis proposes a mechatronics-based framework for development of digital twin production lines,and then a development method of digital twin production lines is proposed based on the framework.Specifically,the development method adopts VUP as the modeling core and Anylogic as the simulation core.In addition,the system test and deployment results are given.The research work in this thesis can be divided into two parts,which are implementation of a digital twin system of the production line and intelligent scheduling of the extended flexible production line,respectively.The detailed contents are as follows:First,the current status of intelligent manufacturing,digital twin production lines and applications of artificial intelligence in intelligent scheduling are reviewed and summarized.The concepts,constituents,and hierarchy of digital twins and digital twin production lines are discussed.The development method of digital twin production line is given,and the corresponding development process is described in detail.Moreover,the development model of digital twin production lines is proposed,and the concrete content of each module in the model is presented.Second,the requirements and functions of the digital twin production line are analyzed based on the mechatronics method,and the basic functions of the digital twin production line are summarized,which act as the development guidance for the subsequent content.Through the data circulation process between the physical production line and the virtual production line,the feedback control function,which is seldom studied in previous digital twin implementation,is deeply analyzed,and the problems and corresponding solutions are given.In addition,system framework of the digital twin production line with feedback control function is proposed.Third,the production line of automobile door handle assembly in our cooperative factory is analyzed.VUP and Any Logic software were selected to jointly develop the digital twin system.According to the basic function requirements of the digital twin production line,functions of monitoring,simulation and feedback are developed,and the detailed development steps of each part of the digital twin system are given.In terms of system implementation and test,the communication and data acquisition technologies of the digital twin system are studied,and the detailed steps of communication implementation and the results of system implementation and testing are given,which validate the feedback control function.Finally,the digital rigid production line of cooperative factory is extended to a flexible one.According to the actual operation of the physical production line,a scheduling model for the flexible production line is constructed,and an intelligent scheduling method based on the deep reinforcement learning DQN algorithm is developed.Simulation results indicate that the proposed method is able to effectively solve the adaptive scheduling problem of the flexible production line.
Keywords/Search Tags:VUP, AnyLogic, Digital Twin Production Line, Implementation and Design, Smart Scheduling
PDF Full Text Request
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