An Ant Colony Algorithm For Balancing Car Interiors Assembly Lines

Assembly line is widely used today as a mode of production. Assembly line balancing problem in the design and operation of assembly line has significant impacts. The balance of the assembly line or not will directly affect the productivity of enterprise manufacturing system, so people in the past few decades did a lot of research on the assembly line balancing problem.Due to the limitation of the dimensions, many enterprises have turned to use two-sided assembly line, especially in large-sized product assembly processes. The two-sided assembly lines have many advantages. For example, it can shorten the length of the assembly line. At the same time, it also can increase the efficiency of workers and fixtures etc. However, the traditional simple assembly line balancing method is no longer applicable to solving the balance problems because of the particularity of its structure, namely the restriction of each element operation directions and operating constraints of the sequence of operations. So in this paper, based on the previous study, put forward a suitable balancing method for the car assembly lines.First, according to the characteristics of two-sided assembly line balancing, a mathematical model was used to describe the assembly line balancing problem. In order to solve the two-sided assembly line balancing problem, it’s not only to consider the cycle time constraints&Precedence relationship constraints as traditional assembly lines, but also synchronization constraints, disjunctive constraints, task side constraints&capacity constraints.Second, according to the particularity of automobile assembly line, the new constraints: constraints of high degree and location of the assembly operations. Third, this paper proposes ant colony algorithm to solve the car assembly line balance problem. Given the complexity of bilateral assembly line and the particularity of the automobile assembly line, we use a heuristic search mechanism of pheromone Combined with the Ranked Positional Weight (RPW), and the program design method as separate processing module before and after. The improved Ant Colony Optimization in this paper used an improved search mechanism, which improved the performance of optimization algorithms and the probability of finding the best solution within the first iteration. To verify the effectiveness of the algorithm,34issues of6questions, from published literatures, were tested in this paper, and the results show that the algorithm can effectively solve the tow-sided assembly line balancing problems. Comparison with the TSA and ACO shows that the improved Ant Colony Optimization in this paper is better than the TSA and ACO.Finally, after observations on the first-line of the CFMA’s automotive assembly line interiors, using the algorithm for optimization to improve the time efficiency of the assembly line.