Integrated Optimization Of Preventive Maintenance And Flexible Flow Shop Group Scheduling Based On ABC-AN Algorithm

As market changes accelerate and differentiated competition intensifies,higher demands are placed on the production efficiency of manufacturing enterprises.A scientific scheduling plan can effectively allocate production resources to maximize production efficiency.A reasonable maintenance plan can provide protection for production activities and ensure the efficiency of production.In previous studies,machine failures are ignored and production activities are scheduled separately,but production activities and maintenance activities occupy machine time.If production activities and maintenance activities are planned separately,time conflicts may occur,causing mutual interference and wrong production plan.Therefore,this paper plans preventive maintenance and production scheduling at the same time,and studies the problem of integrated optimization of preventive maintenance and group scheduling in flow shop under deterministic and uncertain fault conditions.The specific research content is as follows:First,the research background and purpose of this paper in the field of the integration scheduling problem of preventive maintenance and production are described.A review of the existing research in this field is made,and the development trends and shortcomings of the existing research are described.Secondly,with the minimization of the total maximum completion time and the minimization of the total cost as the optimization goals,the integrated optimization problems of preventive maintenance and group scheduling of flow shop under deterministic fault conditions are analyzed and modeled.In the model,the problem assumptions,constraints and so on for the group scheduling problem in flow shop are defined in detail.At the same time,the machine maintenance strategy in the model was formulated.Then,an improved artificial bee colony algorithm with adaptive variable neighborhood search mechanism(ABC-AN)is proposed to solve the problem model in this paper.The adaptive neighborhood search mechanism designed in the algorithm controls and changes the neighborhood search structure in the cycle through adaptive step parameters,according to the current optimization state of the feasible solution to improve the ability of local search and jumping out of the local excellent.Next,integrated optimization model of preventive maintenance and flow shop group scheduling and ABC-AN algorithm proposed in this paper are verified by examples.A multi scale example is designed.The superiority of the integrated model is verified in terms of time and cost by comparing the results of the calculation examples of the integrated optimization model and the separate optimization model.The improvement effect of the algorithm is verified through three benchmark calculation examples and different calculation examples of the proposed model.Finally,the integrated scheduling problem of preventive maintenance and production under uncertain fault is studied.Preventive maintenance plan can effectively improve the reliability of the machine,but random failure is inevitable.On the basis of the problem model in Chapter 2,a proactive robust scheduling model based on game theory is established,which is the first try in this study area.The method includes optimization goal of robustness and efficiency and a buffer time insertion method based on the three-stage bargaining game model.The effect of the model under the influence of different parameters is studied through calculation examples of different scales.In addition,comparing the results of the proactive robust model and the non-proactive model through Monte Carlo simulation,it is verified that the scheduling plan obtained by the proactive model performs better than the non-proactive model after encountering random failures.Therefore,results show that the proactive scheduling plan with buffer time proposed in this paper can effectively reduce the impact of random failures.