Research On Job Shop Scheduling Based On Hybrid Particle Swarm Optimization And Design Management System

Job shop assignment is the process of allocating useful resources in a specified time,including delivery date,processing time and resource capacity.At present,the equipment in the workshop has already replaced a large number of human labor.In the rapid production process,the rapid mobilization of materials and equipment in the workshop is particularly important.Textile industry is an industry with multi-process and complex workshop environment.It is difficult to achieve management because of the large number of machines in the workshop,complex processing procedures and many operators.In the current social environment of green manufacturing,textile industry has to seek a good scheduling method and management system to reduce energy consumption.Therefore,this paper focused on the workshop scheduling problem on textile workshop.The particle swarm optimization algorithm is improved,and optimized the algorithm with Cauchy distribution.According to the actual production environment,the constraint model and objective function is established.The improved algorithm is studied and solved the problem of maintenance interruption in actual production.In order to maximize utilizing workshop resources,a workshop management system is established to integrate the resources and is used to record equipment operation datas.All that will improve the efficiency of workshop management.The details are as follows:(1)The system functions and framework is designed.According to the basic system framework,in the paper,the real workshop production situation is simulated,analyzed the shop scheduling constraints,such as sequence priority constraints,one-time processing constraints and maintenance interruption constraints,and established the mathematical model of the shop scheduling.(2)Based on particle swarm optimization(PSO),the job shop scheduling problem is studied.The first step is to establish the relevant objective function according to the production demand of the workshop.Secondly,the mechanical state is estimated by the historical records of the equipment,and the results would be theconstraint conditions for objective function.Finally,the workshop assignment task is completed by the improved algorithm.Because the particle optimization conforms to the Cauchy distribution,the new particle algorithm connected with Cauchy distribution used to update the speed and position of the particle swarm.Before the iteration stops,the genetic algorithm is used to update the particles by crossover,heredity and mutation,so that the particles converge to the optimal value quickly.(3)Solved the task allocation in workshop with maintenance status,the Dual Particle Swarm Optimization(DPSO)is been considered.Based on the improved particle swarm optimization(PSO),the particles are divided into the main group and the auxiliary group,and the optimal solution is searched by different methods to make the more accurate value.And the maintenance time is predicted based on the Weibull distribution and the data of the mechanical state.In order to shorten the completion cycle,the maintenance time is allocated to the related equipment as the order task.Finally,the effectiveness of the proposed algorithm is proved by applying it to job shop assignment.(4)The workshop management system is developedand.Database is designed to store,update and share data in real time.Based on C++ language,the user interface is designed with UI.And it`s mainly purpose to designed each module by the functional requirements of the system.The whole workshop management system includeds the machine worke state,basic information of workers,displaying production progress,etc.It could also automatically generate scheduling charts by selecting production processes and display them.The management system integrates technology department,production department and personnel department organically,and facilitates operators management and supervision,and also improves management efficiency.