Research And Application On Mixed Flow Workshop Scheduling Problem With Multi-line Shared Resources

With the rapid development of the aviation manufacturing industry,the demands of aviation products continues to diversify,prompting some aviation manufacturing companies to develop multi-varieties and small batch mixed flow manufacturing frameworks.The mixed flow manufacturing mode of aircraft parts does not change the physical layout of the workshop.Besides,this mode can assign processing paths reasonably,schedule production tasks efficiently,and make full use of critical resources.Thus,a logical assembly line can be formed to improve the efficiency of production operations and complete production orders with multiple varieties and small batches.The aircraft parts processing has the characteristics of complex technologies,high quality requirements,emergencies,and expensive key equipment.Therefore,the establishment of a mixed flow production planning and control system is critical to the development of such an enterprise.This paper deeply explores the production planning and scheduling methods of an aircraft parts workshop.A mixed flow workshop planning and operation system for multi-line shared resources is established.The proposed system includes the research of workshop delivery planning,static scheduling,and dynamic scheduling.The TOPSIS method is applied in this paper to solve the workshop delivery planning problem.Equipment load and equipment utilization are used to make a comprehensive evaluation of the production system.Firstly,identify bottlenecks in the workshop.Then,the proposed problem with the objective of minimizing the sum of the bottleneck load variance in different periods is solved by genetic algorithm.Finally,the order distribution can be completed,and the workshop delivery plan can be further obtained.The static scheduling problem of mixed flow production workshop has the characteristics of large-scale,multi-bottleneck and multi-line sharing.Based on the theory of constraints(TOC),this paper simplifies the problem by establishing an equivalent workshop model.This article first establishes the relationship between the actual model and the simplified model.In order to improve the solving efficiency,thispaper improves the traditional genetic algorithm and proposes a new code conversion operation.Computational experiments are performed to examine the performance of the proposed algorithm.The comparison results justify the excellent performance of the presented method regarding the solution quality.The dynamic scheduling problem in this paper includes abnormal events such as equipment breakdown and processing time increasing.In order to solve the proposed problem,several steps are considered in this paper.Firstly,a mathematical programming model is established in combination with the characteristics and constraints of the aircraft parts workshop.Then,combined with the equipment bottleneck load evaluation results,a local search operation is performed to solve this problem.In this paper,the traditional genetic algorithm is improved to enhance the local search ability of the algorithm.Finally,a real-world case is addressed to verify the effectiveness of the improved genetic algorithm.Finally,by taking a real-world aircraft parts workshop as an example,this paper establishes a production planning and scheduling implementation framework for this workshop.The results indicates that the proposed framework has a great implementation effect for a multi-varieties and small batch mixed flow manufacturing system.