Research On Context Recognition Of Reconfigurable Printing Manufacturing Cell And Reconfiguration Scheme Optimization

With the acceleration of the"Intelligent Manufacturing" process and fierce market competition,printing companies must be able to quickly respond to the market's demand for muiltiple varieties,small batches,siort delivery times,and customized printing productionReconfigurable prining manufacturing system provides the best way to achieve this goal.The reconfigurable manufacturing system can not only quickly reorganize or update,adjust the production functions and capabilities of the unit in time to respond to changes in market demand,but also improve product quality,reduce costs,and shorten delivery cycles.Therefore,this project takes the reconfigurable printing manufacturing system as the research object,and coducts research on the status recognition of the reconfigurable printing manufacturing unit and the optimization of reconstruction schemes.The specific works are as follows:(1)This paper analyzes the status of the reconfigurable prining manufacturing unit,extracts the unit features,and then uses Bayesian networks to establish a scene recognition model of the printing manufacturing unit.Different values of network nodes are used to represent the changes in the printing and manufacturing seenarios and unit feature states,the conditional probability is used to represent the probabilistic influence relationship between the unit feature states and the scenarios,so as to realize the recognition of the manufacturing scenarios from the unit feature states.Therefore,it can be judged whether the printing manufacturing unit can meet the requirements of priming quality,production efficiency,etc.according to the existieg prizting procesrrand environmental conditions.(2)According to the actual production factors of printing manufacturing,the comprehensive evaluation model of reconstruction scheme is esiablished.The Analytic Hierarchy Process and lnterval Fuzzy Number weight determination inethods are introduced,the advantages and disadvantages of the two methods are summarized.On this basis,a weight determination method based on triangular fuzzy numbers is proposed to determine the index weights,so as to realize the optimization of reconstruction schemes.This paper simulates the equuipment status and environmental status in the printing workshop.According to the actual printing process requirements,the model is used to judge the printing quality status of the reconfigurable printing manufacturing unit,and finally the validity of the model is verified.In order to determine the optimal reconstruction scheme,the triangular fuzzy number method is used to calculate the index weight.By comparing the rEsuLts of analytic hierarchy process and scene recognitions,the scientific and reliability of the proposed method is verified.