Research On Equipment Management System And Fault Prediction In Foundry Workshop

With the continuous development of society,science and technology continue to advance,and emerging scientific research results are continuously integrated into all aspects of people’s life and production.The foundry workshop is growing rapidly in this thriving environment,equipment as the core asset of the company’s production directly affects the operation costs of the company.The use of advanced network technology,combined with the latest equipment management concepts to achieve scientific management of equipment has become an inevitable trend of equipment management in the foundry workshop.This paper takes the equipment of the foundry workshop of the background company as the research object,and uses the analysis and design method of the management information system to realize the informationization of equipment management.At the same time,it proposes a device fault prediction method for the fault problem.First of all,this paper expounds the background and significance of the topic research,discusses the current research status of equipment management information system and equipment fault prediction at home and abroad.Secondly,the paper analyzes the status quo of the equipment management problem in the foundry and discusses the feasibility of implementing the equipment management system in the workshop,clarifies the construction objectives and construction ideas of the system,determines the specific functional requirements and draws the overall functional structure of the system.Then,the overall structure of the system and the business process of the core module was designed.Through the UML modeling tool,the main functional modules of the workshop were designed using activity diagrams,class diagrams and timing diagrams.Completed the database-related conceptual structure and logical structure design.A device management system with edge computing as the acquisition layer,device management function as the execution layer,and data prediction as the decision layer is constructed.Then,based on the key problem of equipment fault prediction,a fault prediction method based on equipment operating state is proposed.Finally,the implementation effects of the corresponding technologies and related functions used in the development of the system are discussed.The fault prediction method based on GA-LM-BP neural network studied in this paper can predict the running state of equipment better.Combining this method with the equipment management system,this paper proposes a closed-loop system for equipment management from equipment management,data collection to failure prediction using data.The system has been successfully run in the target workshop,verifying the validity of the research content of the article.