The Research Of Production Monitoring And Low-Carbon Scheduling Of Filling Equipment Manufacturing Workshop Based On Internet Of Things

With the rise of smart manufacturing,manufacturing companies are increasingly demanding informationization and intelligence.Facing the complex and volatile workshop production environment,scientific and effective production monitoring is the key and difficult point for enterprises to realize informationization and intelligence.At the same time,in order to deal with environmental degradation and global warming,green sustainable low-carbon manufacturing has become a new development trend of enterprises.Scheduling,as an important part of enterprise production,has a direct impact on the company's production efficiency,energy consumption and carbon emissions.In addition,considering the abnormal disturbances of the workshop in the production process,the enterprise also needs to have the rescheduling ability to deal with these disturbances.This paper takes the filling equipment manufacturing workshop as the research object.For the production monitoring problem,low-carbon scheduling problem and low-carbon rescheduling problem,the main research are as follows:(1)Introduce the research status of production monitoring,low-carbon manufacturing and scheduling at home and abroad.Analyze the problems existing in the current research,and give the main research contents of this paper.(2)Introduce the data acquisition technology of the Internet of Things,and analyze the production monitoring objects of the filling equipment manufacturing workshop.Introduce the concept and characteristics of the scheduling problem,expound the scheduling problem studied in this paper,and describe the common carbon emission sources in the workshop in detail.Based on the problem of shop rescheduling,summarize the common workshop disturbances,and analyze the rescheduling decision method.(3)For the characteristics of production monitoring of the filling equipment manufacturing workshop,analyze the requirements of the production monitoring platform,design the architecture of the platform,build the data collection environment,and optimize the business process of the workshop based on the platform.Define the intelligent manufacturing entity and workshop events in the workshop,introduce the complex event processing engine Esper,and use Esper to realize complex event processing in the workshop.Finally,build the production monitoring platform,and the feasibility of the platform is verified by an example simulation.(4)For the low-carbon scheduling problem of the filling equipment manufacturing workshop,establish a low-carbon scheduling model based on the real-time state of manufacturing resources.Describe the objective function and constraints of the model in detail.Propose an improved multi-objective Jaya optimization algorithm.Discretize the standard Jaya algorithm to solve the shop scheduling problem.Introduce the Tent chaotic sequence method introduced into the algorithm for population initialization,and construct the local search by the combination of neighborhood search and simulated annealing algorithm.Finally,compare with NSGA-II by the workshop instance,verify the effectiveness of the algorithm.Compare with the traditional model without considering the real-time state of manufacturing resources,verify that the model can effectively improve the production efficiency of the workshop and reduce carbon emissions.(5)For the low-carbon rescheduling problem of the filling equipment manufacturing workshop,design the rescheduling judgment method based on delivery time,and introduce the stability index to the rescheduling performance evaluation.Based on the low-carbon scheduling model in Chapter 4,establish a low carbon rescheduling model for the workshop.Improve the simulated annealing genetic algorithm,design and expound initialization process,selection operation,cross operation and mutation operation of the algorithm.Use the benchmark instances and compared with other algorithms to prove the effectiveness of the algorithm.Finally,through the workshop instance,simulate common disturbances such as tooling shortage,machine tool failure and emergency insertion,verify that the rescheduling decision method can effectively deal with the shop abnormal disturbances.