Prediction And Tracing Analysis Method Of Abnormal Discrete Workshop Manufacture In Cloud Manufacturing Environment

With the rapid development of Industrial manufacturing,elements such as cloud computing,Internet of Things,cloud security and artificial intelligence have gradually penetrated into the traditional manufacturing field,forming a new generation of networked manufacturing systems.After the implementation of "Made in China 2025" in China,the manufacturing execution system in the field has become more and more advanced with the integration of various new technologies.Many problems have been solved one by one,and the new model of "cloud manufacturing" networked manufacturing has gradually form.In this environment,the manufacturing execution system conforms to the development trend of intelligent manufacturing and gradually evolves to a networked and distributed direction,forming a new "cloud manufacturing execution system",but some new problems have also arisen from this.For this reason,the manufacturing execution system under the cloud manufacturing environment is deeply studied from the following three aspects.First,the discrete workshop production in the cloud manufacturing environment is variability and uncertainty.Its product production mode is highly customized and the manufacturing process is more complicated.Therefore,t he entire manufacturing process generates a lot of manufacturing data and has multiple sources.,Heterogeneous and other characteristics.During the production process,planning adjustments for different processes and procedures and environmental interference are more frequent,and the problem of information islands in the manufacturing workshop is also more serious.In response to the above problems,a micro-service method of intelligent manufacturing execution system based on domain-driven design is proposed,which uses the high cohesion and autonomy of the micro-service architecture and its specifications,it also combines the ideas of domain-driven design to support manufacturing Users improve production efficiency through service combination.This meth od improves the flexibility,scalability and reliability of the cloud manufacturing execution system.Secondly,discrete workshop manufacturing in the cloud manufacturing environment has weak real-time monitoring and predictive capabilities for production,quality,logistics and other aspects.Therefore,an intelligent prediction method based on workshop production abnormalities in the cloud manufacturing environment is proposed.This method proposes The definition and standards of production abnormalities in discrete workshops are analyzed in detail from the six aspects of production personnel,production equipment,materials,production environment,process flow,and inspection process.)The production abnormality prediction model takes the abnormal impression factors of cloud manufacturing resources as input,outputs the product abnormal prediction value and completes the intelligent prediction of production abnormalities in accordance with quality standards.This method improves the accuracy of productio n abnormality prediction and can effectively guarantee the economic benefits of manufacturing enterprises.Finally,in order to improve the discrete workshop manufacturing system architecture in the cloud manufacturing environment and further improve the quality diagnosis and traceability capabilities of discrete workshop manufacturing,a causal chain-based model and method for traceability of workshop production abnormalities is proposed.This method designs a method for constructing a causal chain model of abnormal production in the workshop,it also provides a corresponding data discretization preprocessing scheme.By applying the established causal chain model to the joint tree algorithm,the traceability of workshop production abnormalities is completed.Numerical simulation experiments have proved that the method has good performance and can effectively feedback the abnormal processes and procedures in the whole process of discrete workshop production.Finally,based on the above three parts,a micro-service manufacturing execution system in a cloud manufacturing environment is constructed,and a detailed and specific system design scheme and implementation scheme are given.To sum up,this article combines domain-driven design of micro-service architecture,time convolutional network,causal chain,joint tree algorithm and other technologies to help the intelligent manufacturing execution system in the cloud manufacturing environment micro-service,discrete workshop production abnormal Three improvements in intelligent prediction and the traceability of production anomalies in discrete workshops provide specific and effective solutions.It has improved the network and informatization of the new generation of intelligent manufacturing systems and promoted the integration of cloud computing and manufacturing.