Research On Permutation Flow Shop Scheduling Problem Considering Maintenance Restriction

As the concept of "made in C hina 2025" and "industry 4.0" in Germany comes up,the equipment gradually became an important factor affecting the production schedule of the whole workshop.Permutation Flow Shop scheduling Problem(PFSP)is a classic Problem in the field of Shop scheduling,it has an important theoretical and practica l significance.In this paper,based on the preventive maintenance strategy of the equipment,the integrated optimization model of PFSP production scheduling and preventive maintenance is established to minimize the maximum time of the system.Firstly,the relationship between equipment failure rate and equivalent age is pointed out by theoretical analysis,then the equipment failure rate function based on equivalent age is established,and the effectiveness is Proved.Secondly,in order to arrange the best time of preventive maintenance,(0,N)strategy model is established to minimize Unit time maintenance cost.Thirdly,based on the minimization of the maximum completion time of the system,the integrated mathematical model of the replacement flow shop is established.Finally,the deficiency of the differential evolution algorithm in solving the complex model is studied.Based on the reverse learning mechanism and Population clustering,an improved adaptive differential evolution algorithm is proposed to increase the diversity of individuals and local search ability,and then improve the effectiveness of the algorithm in solving the integrated model.In the case study,The model is solved by collecting the basic data of the production department and the maintenance department of the I company.Firstly,based on the preventive maintenance strategy model,the preventive maintenance period and the maximum maintenance times of each cycle are obtained.Then,the improved adaptive differential evolution algorithm is used to solve the integrated model to find the best order combination and preventive maintenance position.Finally,in order to verify the effectiveness of the improved algorithm in this paper,we compare the results of the standard differential evolution algorithm with different workpiece scale.The results show that with the increase of the workpiece size,the improved difference evolution algorithm can give a better solution.We compare the scheduling model currently used by I company with the inte grated model in this paper,the effectiveness of the integrated model is proved.