A variety of factors will affect the combination and distribution of the molds used in the production of prefabricated components on the mold table, and will produce many combination and distribution results. In order to solve such problems and quickly find the best distribution results of the molds on the mold table, this paper proposed a mold combination method based on the combination of backtracking method and improved Eclat algorithm. Firstly, it built a binary tree model based on the mold combination relationship in the historical data, searched the binary tree through the backtracking method, and obtained all theoretically feasible mold combination results. Then it pre-placed these combination results by using the improved BL positioning algorithm on the mold table with a fixed area, and screened out the mold combination results that met the actual placement conditions. It used Eclat algorithm to obtain the optimal combination set of mold adaptation from the selected combination results, determined the association rules between different types of molds, and used the rules to guide the allocation process of molds on the mold table in the new component production task. At the same time, this paper improved the Eclat algorithm by introducing the partition idea and the priori constraint idea based on probability, so as to improve its operation efficiency when dealing with large-scale data. Finally, through the simulation test of the case data in the prefabricated component manufacturing enterprise, it verified the effectiveness of the method to quickly solve the problem of mold table combination allocation. The results show that the mold combination allocation based on backtracking and DEclat algorithm method has a good effect on the utilization of the mold area, the reduction of the mold changing time and the reduction of the total completion time.

[2022-11-09] Accepted Paper /doc/2022.09.0437/v1

[2023-05-05] Printed Article /doc/2022.09.0437/v2