Research On The Job Shop Scheduling Under MTO Environment Based On Group Technology

With the increasingly fierce marketing competition, manufacturers have to switch from the traditional large-scale inventory oriented production mode to the order oriented production mode, so as to respond to the market demand in a more flexible way. However, the order oriented production mode often has many kinds of products, the production process and greatly increases the complexity of production scheduling, which greatly improves the complexity of production scheduling. In group technology, the similarity of objects is discovered, which provides an effective means to solve the problem of order type job shop scheduling problem by grouping similar problems into groups. Based on the group technology,this thesis studies the Shop Job scheduling problem in multi variety, small batch and order manufacturing environment.According to the characteristics of order manufacturing, the concept of “virtual parts” is proposed. The virtual part is packaged together with the attributes of the workpiece to form a workpiece which can be processed together. On the other hand, virtual part of introduction can simplify the complexity of the product structure, increase the granularity of the scheduling objectives, reduce the size of the scheduling problem, reduce the workpiece preparation time and improve the scheduling performance. On the basis of this, the order form Shop Job scheduling model, which is based on the virtual part, is set up with the production resource constraints.Based on virtual parts, this thesis analyzes the scheduling policy from two aspects: the order group and the work piece group. Order grouping strategy considers the similarity of order processing period, the product structure and the constraint conditions of production capacity, and puts forward the strategy of order grouping. According to the same method of the core processing resources and the same method of processing resources, the group results are analyzed, and the corresponding work pieces are obtained.In order to solve the Shop Job scheduling problem, an improved ant colony algorithm is proposed in this thesis, which is introduced into the elite ant, namely, the ants which produce the global optimal solution in each cycle to release additional pheromone. Compared with thetraditional ant colony algorithm, the improved algorithm is superior to the traditional ant colony algorithm in terms of convergence, search efficiency and search results.This thesis conducts the simulation research on the order grouping of job shop scheduling problem. The results show that the improved ant colony algorithm support, order grouping strategies and job grouping strategy applied to the order of job shop problem, to ensure the performance of the job shop scheduling to improve under the premise of order completion period, effectively reduce the order completion time and delivery time.