| With the development of computer technology and information technology,workshop information management technology has made great progress.However,with the increase of product complexity in manufacturing industry,the workshop operation scheduling problem and material distribution path planning problem are still the key and difficult points of workshop information management,which have far-reaching influence on improving workshop production efficiency and increasing enterprise benefits,and have important research significance and value.Many orders in the workshop production process must be guaranteed to be completed on schedule(such orders are called orders with mandatory nodes).Once these orders are not delivered on time,it will have a great impact on the enterprise efficiency.Just-in-time material delivery is the guarantee of smooth production activities on the shop floor.Early delivery is likely to cause a backlog of materials at workstations,and delayed delivery may interrupt processing.At present,heuristic algorithms are generally used to solve the shop operation scheduling problem,but these algorithms do not consider the order compulsory nodes and ignore the shop processing machine selection problem.In addition,intelligent algorithms are generally used to solve material distribution path planning problems with time window constraints,e.g.,genetic algorithms,ant colony algorithms,etc.,but the convergence speed of the algorithms is slow and not suitable for solving complex problems.Therefore,this thesis will analyze the machine selection problem in the process processing and study the job scheduling algorithm with forced nodes.The shop floor material distribution path planning problem with time window constraints is studied.In addition,the shop floor job scheduling algorithm and material distribution path planning algorithm are used as the core to design and implement the shop floor scheduling management system.First,the order priority-based job scheduling algorithm is designed for the shop floor job scheduling problem considering mandatory node and machine selection.The algorithm designs the order priority calculation formula,which can guarantee the priority processing of orders with mandatory nodes.For the equipment selection problem,the traditional hierarchical analysis method is improved by considering various influencing factors.The improved hierarchical analysis method can automatically construct a consistency discriminant matrix according to the equipment status,and then select the appropriate processing equipment for the process.The experiment proves that the algorithm can effectively solve the shop operation scheduling problem considering forced nodes and machine selection.Second,for the shop floor material distribution route planning problem with time window constraints,a genetic algorithm based on adaptive crossover operator and adaptive variation operator is designed.Firstly,the mathematical model is established according to the constraints,and then the adaptive crossover operator and adaptive variation operator are designed according to the characteristics of different evolutionary stages of the genetic algorithm.Finally,it is proved experimentally that the calculation results of the improved genetic algorithm have higher full load rate and lower distribution cost compared with the real scheduling scheme;and have better convergence and convergence speed compared with the classical genetic algorithm.Finally,with the shop operation scheduling algorithm and improved genetic algorithm studied in this thesis as the core,a structured design method is used to design the overall structure of the system,the functional modules of the system are designed using IPO diagram,the database design is completed through database conceptual design,logical design and physical design,and finally the database design is completed through Microsoft SQL Server2017 database and Microsoft Visual Studio2010 system development platform to realize the workshop scheduling management system under MES system. |
PDF Full Text Request