Optimization And Simulation Of Auto Mixed-Flow Production System

As car consumers increasingly tend to individual needs and service, automobile industry production patterns also gradually shift from mass production to many varieties of small batch production, which is in order to meet the demand of customers. Together with the continuously shortening of the cycle of products update and in-depth promotion of JIT(Just-In-Time) mode in the car industry, it's malapropos to reengineer production lines for each product, and the cost is too high.And mixed-flow production can be a good solution to this problem. The key to guaranteeing the normal operation of mixed-flow production is leveling production, and production sequence of different products is the key factor for leveling production.Therefore, this paper takes the auto mixed-flow assembly production sequence for example, making a comparison of the two algorithms based on the mathematical modeling.And then the computer simulation is used to test the two schemes in order to find a simple and practical method for auto mixed-flow production sequence.This paper firstly introduces the research background of mixed-flow production and the study situation both at home and abroad, the paper expounds the concept characteristics and operation mode of mixed-flow production, and illustrates the implementation of leveling production for automobile industry based on JIT, and the influence of JIT on auto industry. In addition, according to different targets different strategys will be selected for auto mixed-flow production sequence.This paper aims keeping balance of the unilization of the spare parts of the mixed-flow prodcut line.According to a case of auto production sequence,firstly,this paper establishes the mathematical model according to the target.Then, c++is used to programm to get a production sequence according to the Goal Chasing Algorithm and get another sequence through Lingo software. Finally,a auto mixed-flow production model is built by using Flexsim simulation software to reflect the consumption of the spare parts intuitively during the production process.The results of the two production sequences show that through Lingo software can be get a optimal solution and the desired value is smaller, program commonality is also better. And a auto mixed-flow production model established by Flexsim software provides more intuitive basis to verify and compare the two production sequences.The conclusion shows that using mathematical programming method by Lingo software can get a better result than Goal Chasing Algorithm,and the commonality of the program in Lingo is better too.In practical production, only change the initial datas can we get a production sequence, and we can test it through simulation model. Therefore, the research in this paper has certain theoretical and practical significances.