Development And Selection Of Flexible Job-shop Rescheduling Schemes Considering Multiple Disturbances

With the continuous upgrading of market demand levels,the demand for personalized,quality and diversified products has proliferated.In order to adapt to market changes,many enterprises have transformed to a multi-species,small and medium-sized production mode.The flexible job shop is widely chosen as a production organization model with high flexibility and the ability to quickly adjust production processes in response to changes in market demand and customer orders.However,there are many uncertainties in the actual production process that affect the normal production activities of the workshop,and when the impact is greater a new production plan needs to be developed to guide the workshop production.Rescheduling,as a scheduling method that adjusts and rearranges according to actual production conditions,is highly applicable in dynamic and changing production environments and can maximize production efficiency and capacity utilization,so it is important to consider multiple factors to develop a rescheduling plan.From the existing research,most of the studies on the formulation and selection of rescheduling solutions for uncertain disturbances adopt a single strategy to cope with multiple disturbances or consider only one type of disturbance events,and the solutions have problems such as poor flexibility and low adaptability;at the same time,they mostly adopt random methods or fuzzy number sets to select the optimal solution,ignoring the characteristics of disturbances themselves,and do not take into account the comprehensive consideration of enterprise preferences and objective production requirements,which does not meet the actual production needs.To address the above problems,this thesis conducts research on the formulation and selection of flexible job shop rescheduling schemes considering multiple disturbances.To effectively solve the problems of poor flexibility,weak guidance and low adaptability of the rescheduling scheme considering only one type of disturbance event or using a single strategy,this thesis proposes a rescheduling scheme formulation method considering multiple disturbances on the basis of existing research.The method classifies disturbances according to the sources of disturbance events and formulates a set of various disturbance response strategies.Based on this method,a rescheduling model with different policies is constructed with the objectives of maximum completion time z and minimum machine load balancing rate,and an improved artificial bee colony algorithm is designed to solve the model.The algorithm solves the problem that the standard artificial bee colony algorithm tends to fall into local optimum by adopting a hybrid initialization strategy,and introduces external solution sets to make it applicable to multi-objective problem solving.The method is able to solve the rescheduling model with different strategies based on the disturbance characteristics after the occurrence of the disturbance,to formulate an appropriate rescheduling scheme,and to provide an alternative rescheduling scheme for subsequent rescheduling options.In order to select the most scientific and effective rescheduling solution that best meets the current disturbance impact elimination requirements,a rescheduling solution selection method based on G1-improved entropy weight method-improved TOPSIS considering processing time,machine utilization,loss cost and machine energy consumption is proposed,taking into account enterprise preferences and objective production requirements.The method quantifies and selects the alternative rescheduling solutions through a comprehensive performance evaluation index.The inverse entropy weighting method is used to improve the entropy weighting method,and the minimum differentiation theory is used in conjunction with the G1 method to determine the comprehensive weights of each performance evaluation index based on enterprise preference and the objective index value of the solution.On this basis,TOPSIS,which introduces KL scatter theory and grey correlation theory,is used to evaluate the advantages and disadvantages of the alternative rescheduling schemes obtained from the rescheduling scheme development method,and to select the disturbance response rescheduling scheme that meets both objective production requirements and enterprise preferences.To verify the effectiveness of the method proposed in this thesis,a production example of W’s diesel engine block machining workshop was used to validate the method.The relevant production data obtained from the practical research was integrated and analyzed,and the method was applied to the example of fault disturbance and new order insertion.The performance of the rescheduling solution obtained from the above method was compared with the actual production rescheduling solution of the company,and the results showed that the re-scheduling solution proposed in this thesis had better overall performance in terms of processing time,machine utilization,wear and tear costs and machine energy consumption,which verified the feasibility and effectiveness of the method proposed in this thesis.The results show that the rescheduling solution proposed in this thesis has better overall performance in terms of processing time,machine utilization,loss cost and machine energy consumption.The rescheduling plan formulation and selection method proposed in this thesis improves the global and flexibility of the rescheduling plan and promotes the long-term effective development of the enterprise while ensuring the production efficiency,which has certain practical significance and theoretical value,and has certain reference and reference significance for related enterprises.