Research On Integrated Problem Of Scheduling And Preventive Maintenance In Deteriorating Flowshop

Traditional manufacturing industry is facing great challenges in transformation and upgrading with the development of intelligent manufacturing.The rational allocation of resources and energy is important for industrial development.There is a problem of mutual influence or even conflict between production scheduling and maintenance tasks in the actual production system.Production and processing will degrade equipment,increase equipment failure rate.In production,maintenances are needed to reduce equipment failure rate and maintain the stable operation of the equipment.While,maintenances activities occupy the production time of equipment,resulting in additional consumption of production resources.Therefore,coordinating production and maintenance is significant to improve the efficiency of the manufacturing system,protect equipment,saving production costs,and realize the optimal use of resources and energy.In this thesis,the integrated problem of scheduling and maintenance in Flowshop is studied as follows:(1)This thesis takes the deteriorating Flowshop as the research object.A mathematical model with the objective of minimizing the makespan and average idle time of equipment is established.The makespan and average idle time of equipment respectively represent production and maintenance departments.(2)In order to describe the equipment degradation and sudden failures in the production,the equipment reliability theory is introduced,and the equipment failure function is assumed to follow weibull distribution.The function of failure rate and enlistment age is used to describe the decline of equipment.The degradation model of processing time and preventive maintenance time is established with the degradation of the equipment and flexible preventive maintenance.With considering the equipment reliability,the task is to determine the scheduling plan and preventive maintenance plan.(3)Based on NSGA-II(Non-dominated Sorting based Genetic Algorithm,NSGA-II),a multi-objective hybrid algorithm combined diversity solutions is designed to avoid trapping in local Pareto optimum frontier.The retention strategy can be described as increasing the proportion of diversity solutions to expand the search space in the early iteration,increasing the proportion of good-quality solutions to improve algorithm accuracy in the end iteration.Order crossover operator is designed to preserve the positional sequence of the workpieces,2-optimization operator is proposed to improve the Pareto front solutions.(4)Experiments of different sizes are designed to verify the model and the proposed algorithm,take the minimum spread range and the interval distance of optimal Pareto solutions as the evaluation index of multi-objective optimization algorithm.The comparisons between the NSGA-II and the proposed algorithm shows that the proposed algorithm can obtain more Pareto solutions and run faster,the proposed algorithm preforms better in convergence and diversity.The proposed algorithm provides a production plan with less equipment idle time and earlier maximum completion time,which reduces resource waste during production scheduling and maintenance.