| Auto parts spraying is an important link in the production process of auto parts.Optimizing the production of auto parts color spraying will help companies further reduce production costs.There is currently no literature that proposes targeted mathematical models and solutions to this type of problem.Therefore,it is of theoretical guiding significance for the actual production to put forward an efficient solution method for the actual problems of the spraying production of auto parts.Firstly,the actual single-wheel steam parts spraying production problem is transformed into a mathematical problem.Considering that each steam part must be sprayed and only sprayed once,it has the basic characteristics of the traveling salesman problem(TSP).The optimization problem of spraying production of single-wheel steam parts is transformed and modeled.The auto parts are defined as the TSP vertices,and the distance between the vertices and production constraints are defined according to the color and category requirements of the auto parts,thereby a 0-1 planning model that minimizes the number of color switching times for single-wheel spray production is constructed.Secondly,for a batch of auto parts to be sprayed with a quantity greater than the production capacity of one round of spraying on a production line,first "packing them" into auto parts groups,and then quantifing all the various parts groups in different colors,with the upper limit of the number of each specific bracket as the constraint,with the goal of reducing the number of stent replacements,an allocation model is established.Then define the auto parts groups that need to be placed on the same skid to be sprayed as the vertices of the TSP.Just liked the single-wheel auto parts spraying production,the color and type adjacency requirements are the constraints,and the minimum number of the overall color switching times are the objective function,then the TSP transformation model for multi-wheel spray production is established.Then,the color and category constraints of auto parts are converted into penalty factors to form the fitness function of the genetic algorithm.Based on the championship selection strategy,the gene crossover and mutation operators of copying,swapping,flipping,and sliding are comprehensively designed.Three sets of data auto parts of different scales that can be sprayed in one round are constructed for simulation experiments,and the algorithms can all obtain accurate and optimal solutions.Repeatedly running the algorithm,the average value of the approximate optimal solution is close to the optimal solution.The experimental results show that the mathematical model is accurate and the designed genetic algorithm is efficient and practical.Finally,based on the distribution model,the auto parts groups that need to be sprayed for multiple rounds is solved by the distribution algorithm to obtain the spraying tasks and the total number of bracket replacements.The genetic algorithm is still used to solve the spraying production problem for each wheel of the auto parts group after the allocation,and the cost of violating constraints is reduced by adding empty skis.The algorithm can find the approximate optimal solution and the number of color changes per round.Experimental results show that the algorithm and model effectively reduce production costs,and can be extended to other similar production and processing problems. |
