Il processo di produzione delle parti aerospaziali Pianificazione del percorso
The part contains several machining features, and each machining feature has several corresponding machining methods and manufacturing resources.
The main research content of process route planning is to select suitable machining methods and manufacturing resources for machining features and sort them to reduce machining costs. It should be noted that the process route is not equivalent to the process table. It only discusses the machining sequence of machining features, the selection of machining methods and manufacturing resources, and does not involve specific machining content such as tool path design and cutting parameters. Process route planning is a NP difficulty Hamiltonian path problem [, and in engineering practice, it is restricted by many process rules. Therefore, when planning the process route, most documents divide it into two parts for consideration: firstly, ensure that the process route meets the constraints of the process rules; secondly, optimize the process route and reduce its machining cost as much as possible. In the process route planning, heuristic algorithms are mostly used. In the algorithm, the factors that undermine the feasibility of the process route mainly exist in two aspects. On the one hand, when the initial process route is generated, a completely random generation method will generate a part of the rules that do not conform to the rules. Process route. In this regard, the edge selection strategy is used to generate the initial process route. According to the process step priority map, the initial plan is generated through the random topological sorting algorithm. Based on the multi-color set theory, the process step sorting rule is expressed by the method of constructing a fenced Boolean matrix. Generating the initial process route effectively improves the generation efficiency of the initial process route.
On the other hand, the neighborhood search method with no rule constraints will also generate process routes that do not conform to the rules. For this, the feasibility review method is adopted. After each iteration of the algorithm is completed, the non-conforming process will be eliminated according to the process sequence rules. A program that meets the requirements. Dou Jianping adopts the sub-sequence cross-mutation method, and uses the feasible sequence of the process route to guide the mutation, which effectively guarantees
The feasibility of the offspring. In addition, in order to express more clearly the constraints of the rules on the sequence of steps, a priority matrix has been formulated according to the ordering rules of the steps to make the processo di lavorazione more standardized and simpler. In the research on the optimization method of the process route, the replacement frequency of the machine tool, the tool and the feed direction and the consumption caused by the resource use are used as the evaluation factor to construct the objective function, and the particle swarm algorithm is used for optimization. At the same time, the machining cost and time cost are considered, and the scheme is optimized based on the process constraint matrix established by the constraints of characteristics and machining methods, and the particle swarm algorithm is used for optimization. Divide the levels of many factors that affect the quality of the process route, and use the method of fuzzy comprehensive evaluation to achieve decision optimization.
According to the above-mentioned literature analysis, the mainstream methods of process route planning are genetic algorithm (GA), artificial immune algorithm (Artificial Immune System, AIS) and other intelligent algorithms. Although intelligent algorithms have developed rapidly in recent years, Because the process model is relatively complex, the application in the field of process route planning has not reached a relatively mature level, and the research potential is great. The problem handling mechanism of intelligent algorithms still has the following problems:
- (1) The intelligent algorithm does not make full use of the prior knowledge of the process field, which leads to a large amount of calculations in order to construct a set of feasible process routes.
- (2) The imbalance in the distribution of feasible process routes is easily magnified by the mechanism based on affinity, especially the large number of features of spacecraft shell parts, leading to potential process routes being easily eliminated and falling into a local optimum.
- (3) It did not consider the existence of different machining methods for the same feature, including the impact on machining costs, and the machining methods of different machining methods in the process route planning. Therefore, on the basis of ensuring the feasibility of the process route, optimize and adjust it to obtain a low-cost process route, which is the main research content of this article.