Research And Development Of Big Production Data Processing System For Workshop In Cloud Manufacturing Environment

With the in-depth promotion of Industry 4.0,Made in China 2025 and other advanced manufacturing concept,the manufacturing industry is stimulated to develop towards the direction of digitalization and intelligence.In this context,it is particularly important to realize the efficient utilization of workshop production data.Traditional manufacturing workshops have some problems like discrete distribution of resources,incomplete representation of functional features and low flexibility,which greatly limit the intelligent development of the workshop.This thesis studies the cloud manufacturing theory,designs and constructs a workshop production big data processing system that combines multisource heterogeneous production data acquisition,low delay data transmission,running streaming calculation and batch calculation in parallel.In view of the characteristics of various types and forms of workshop manufacturing resources,a resource virtualization model is designed to describe the manufacturing resources uniformly.Based on the classification results and attribute description information of manufacturing resources,a structural model of manufacturing resources is constructed by modelling tools.The interface of resource creation is designed to receive the static attributes of the resource,and the resource instance is encapsulated by XML language.Appropriate acquisition modules are developed for each kind of data and the edge computing module is designed to reduce the amount of data transmission and the abstract data interface is designed to improve the extensibility and flexibility of the system.In order to overcome the problems of high delay of data transmission and single processing mode existing in the traditional data system of workshop,the big data transmission and processing systems are designed and developed for workshop production in this thesis.The framework of data transmission system is built by using distributed messaging middleware Kafka.A series of functional modules have been designed and developed to realize the functions of data shunting,message filtering and easy-to-use data receiving and sending interface.In order to satisfy the real-time and accuracy requirements of the production data processing results in the workshop,a data processing system based on Lambda architecture is designed to parallelly run streaming computation and batch computation.The production status monitoring module is developed to monitor the production environment,equipment running status and workpiece processing flow of the workshop,so as to realize the transparency of the production status of the workshop.On the basis of the above research,the system deployment,performance test and the design of resource virtualization module are completed.By introducing the micro-service architecture to deploy the system which can reduce the coupling degree between each functional module.Throughput and average delay of the data transmission system are tested comprehensively through experiments,and the availability of the system is verified.Based on the framework of Spring Boot,the interface of resource creation and query is designed.By combining with the data collection system and the data processing system,the static and dynamic attributes of manufacturing resources can be merged,and the description accuracy of the resource virtualization model can be improved.