Mixed assembly sequence generation method based on symbols

Abstract

The invention discloses a mixed assembly sequence generation method based on symbols. The method comprises steps of establishing a ZBDD expression of a connection matrix and an interference matrix according to the connection matrix and the interference matrix of an assembly; solving a precedence relation matrix in dependence on the interference matrix of the assembly; searching all feasible assembly sequences, establishing a file for storing the feasible assembly sequences and subassemblies generated in the assembly process, and establishing a dynamic array for storing path numbers for generating the subassemblies; and refining the established file for storing the feasible assembly sequences and the subassemblies, and deleting dead states in the assembly process. The invention can ensure completeness of assembly sequences by analyzing all possible assembly operations at the high space and time efficiency, ensure reliability of the assembly sequences by determining local assembly geometric feasibility, ensure high efficiency of an algorithm by determining satisfiability of a precedence relation, and finally complete generation of all the feasible assembly sequences of the assembly.

Description

technical field [0001] The invention relates to the technical field of assembly sequence planning, in particular to a method for generating a mixed assembly sequence based on symbols. Background technique [0002] Assembly Sequence Planning (Assembly Sequence Planning, ASP) is a technical difficulty in assembly planning, which occupies a very important position in the process of product design, development and production. For the production of large-scale products, an excellent assembly sequence will greatly shorten the production cycle of the product, reduce the production cost of the product, and improve the quality and performance of the product. ASP is a highly constrained NP combinatorial optimization problem. The selection of the assembly sequence must follow the geometric constraints between the parts, and the complexity of the exhaustive search algorithm is exponential. When the product is relatively complex and has a large number of parts, the problem of state comb...

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Problems solved by technology

If the generation of such subassemblies is not prevented in advance, more infeasible subassemblies may appear later, resulting in various dead states (non-final states, but no successor states) after the search ends.

Therefore, it is necessary to backtrack and delete all dead states, and when the number of infeasible subassemblies is large, it is more complicated to deal with dead states at the end, which will reduce the solution efficiency and solution scale of the assembly sequence planning problem

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