Research And Application Of Some Key Technology Of MES System In Tire Enterprise

Under the general trend of rapid development of domestic economy and global economic integration,the competition among tire enterprises is more and more intense.Only by constantly improving their manufacturing capabilities to meet the demands of customers' real-time changes,can they stand out from this.In recent years,the application of management systems such as ERP,SCM and CRM has reached a certain level.However,there is still a big gap in the information and intelligence in manufacturing fields.The key technology research and application of Manufacturing Execution System(MES)is still a weakness.It can be said that MES system has been paid attention to by more and more manufacturing enterprises,and it is urgent for tire enterprises to establish a set of MES systems consistent with their own production characteristics.The research and application in this paper come from the cooperative project between our university and a large tire manufacturing enterprise,who serves as the application scenarios to develop and implement MES in tire production.The first chapter starts from the background analysis,then discusses the definition of MES,the history of this topic.It also summarizes the current research and application of MES at home and abroad,and points out the existing problems,from which the main contents and the architecture of this paper are presented.The second chapter discusses some key technology applications of MES system,including product models of tire manufacturing,field data automatic acquisition,Drools rule engine and deep learning.Some key technologies are still under development.The former researches the product model during the tire manufacturing process,describes the related technical specifications of various types of tires,the prescription relationship between the materials of the tire,and the relationship between various components,and designed the BOM tire chart,the E-R chart,and data table structure based on automatic acquisition technology.We introduces the principle of field data automatic acquisition system,and according to the specific circumstances of the workshop in the production process of tire,we achieved the automatic gathering of field data in each link of tire productionwith the application of barcode technology and wireless RFID technology.Drools rule engine technology is an open source business rules engine,which can transform complex conditional statements in the program into the form of rules.In order to facilitate the management procedures,we explore the application of Drools to the tire production planning schedule,based on rules of non-zero production priority and sales classification emergency priority for tire production plan.We applied Drools to efficiently manage rules.Deep learning technology is a new technology whose application is more mature in artificial intelligence domain.We applied convolution neural network(CNN)technology in deep learning to the X-ray detection of tire product flaws,and collected some kinds of common defects of the tire sample to train the network model,and achieved reasonable effects in the automatic detection of tire defects.The third chapter is based on the production status of a large tire manufacturer in Hangzhou,and presents the overall architecture and function module design of the system of tire MES system,including process monitoring,production management,statistical reports,equipment management,quality management,material management,product model.The design satisfied with both the hardware and software environment and the non-functional requirement of the MES system.The fourth chapter summarizes the common problems during the implementation of MES system in our cooperation tire manufacturer,so as to draw lessons for other peers.Finally,it analyzes the benefits of MES implementation in this tire manufacture.The fifth chapter is the conclusion.First,the related works and achievements of this paper are summarized.Finally,the future improvement direction of the MES system is put forward,and the future trends of MES is discussed.