Research On Failure Prediction And Maintenance Decision Of Manufacturing Unit Equipment

With the development of the economy,the individualized demand of customers is becoming more and more obvious.The manufacturing unit is the production unit that can meet the individualized needs of the market to the greatest extent.The development of technologies such as the Internet of Things and big data has made intelligent manufacturing possible.Therefore,intelligent manufacturing units are the trend of manufacturing enterprises.Equipments are the core of manufacturing enterprise.Maintenance management of equipment has always been a hot issue for manufacturing companies.Advances in technology have made equipments more complex and intelligent,which has brought new challenges to enterprise equipment maintenance management.In order to adapt to this change,this paper proposes a joint equipment maintenance problem for intelligent manufacturing unit equipment,which is a frontier subject in related fields such as management.This paper has studied the question of the fault prediction of equipment and the decision of joint equipment maintenance in intelligent manufacturing unit multi-equipment system,which based on Internet of Things and big data.This paper establishes related mathematical models,which effectively solves the problem of system downtime loss caused by the different preventive maintenance intervals of each device in a multi-device system.This article is based on previous research,relying on the background of Internet of Things and big data technology.This paper draws on the concept of Fault prediction and Health Management technology(PHM).It also draws on the mature equipment maintenance theory and solutions to scientific problems in other disciplines.This article studies the joint equipment maintenance problem.The specific research contents of this paper are as follows:(1)This paper introduces the organization of the multi-equipment system of the manufacturing unit.The failure prediction technology and the influencing factors of maintenance decision-making for the long-term development of equipment maintenance are analyzed.This paper also illustrates the source of data for failure prediction of equipments in intelligent manufacturing unit;(2)A model for joint equipment monitoring of intelligent manufacturing unit multi-equipment systems is proposed.The previous methods of fault prediction are analyzed and compared.In this paper,the Bayesian network is used to predict the fault of the equipment.The fault prediction process based on Bayesian network is given.And the effectiveness of the method for fault prediction of equipment is illustrated by an example.(3)Compare the results of fault prediction with equipment failure thresholds.Preventive maintenance of equipment will be performed when the predicted result is greater than the equipment failure threshold.This paper combined with the characteristics of the multi-equipment system of the manufacturing unit,establishing a model to minimize the total maintenance cost of the system,and constraining the availability of the equipment and the reliability of the system.The validity of the model is verified by an example.Ultimately get the optimal preventive maintenance interval for the system.