Research On Joint Optimization Of Prefabricated Component Production Scheduling And Equipment Preventive Maintenance

To achieve sustainable development,prefabricated construction was actively promoted in our country.But the production management of prefabricated building is inefficient,lack of scientific and effective guidance.The problems of unreasonable production scheduling and low production efficiency are common in the production process of prefabricated components,which not only increase the production cost of prefabricated components,but also restrict the development of prefabricated buildings.Therefore,to realize scientific and effective management and make reasonable production scheduling of prefabricated components are significant to the further development of prefabricated buildings.Based on the analysis of the production process and process characteristics of prefabricated building components,a production scheduling model of prefabricated components is established.Considering the impact of worker learning on processing time in the production process,the scheduling model introduced a learning effect.In order to more closely conform to the production practice,based on the relationship between production scheduling and equipment maintenance,considering the equipment maintenance,a joint optimization model of prefabricated production scheduling and equipment preventive maintenance was constructed to minimize the total completion time,minimize total penalty cost and minimize the total maintenance cost.And the production scheduling sequence and preventive maintenance decision sequence of prefabricated components can be made jointly and optimized.Then,a multi-objective backbone particle swarm optimization algorithm(BB-MOPSO)was improved and designed to solve the joint optimization model in which integer encoding based on ranked-order value(ROV)rule and congestion-tournament selection method is used,besides,the time-varying mutation operator is introduced to increase the population diversity.Then,the results of the proposed algorithm were compared with the results of the NSGA-?(rapid non dominated sorting genetic algorithm),which widely solving the multi-objective problems,by using multi-objective test functions.The results show that the proposed algorithm has better performance.Finally,the model and algorithm were applied to the actual production case of X company in shanxi province,and MATLAB software was used for simulation.Compared with the results of the independent decision model,the results show that a better solution can be obtained by using the joint optimization model in this paper,and the optimization effect is the best in terms of the total maintenance cost,and the optimization rate is up to20.77%.It is proved that the joint model can provide a more satisfactory production scheme for decision makers,and the rationality and effectiveness of the model are verified.To test and verify the feasibility and validity of this algorithm,the proposed algorithm was compared with the NSGA-?on 5 kinds of performance evaluation index and the iterative process of various.The comparison results show that the performance of the proposed algorithm is better in convergence,search ability and non-dominant solution set distribution.The research of this paper provides a new method and idea for the prefabricated component manufacturing enterprises to make production scheduling and preventive maintenance plan of equipment,and provides a new solution method for solving the practical multi-objective optimization problem.