A novel assembly sequence evaluation and planning method in high-speed winding spindle assembly using hybrid metaheuristic algorithm

Abstract

The assembly precision of the spindle has a direct impact on quality and performance of the high-speed winder. Assembly sequence is one of the key influencing factors. In actual production activities, the spindle assembly of high-speed winder has the characteristics of numerous parts and long process, which easily leads to illogical arrangement of assembly sequences and a high reassembly rate. In this paper, for the issue of assembly sequence planning (ASP), a novel assembly sequence evaluation system was established, and an ASP algorithm was designed. Firstly, the structure and assembly characteristics of spindle were analyzed. Then, an evaluation system for planning assembly sequences was built, taking into consideration two key factors: assembly efficiency and quality. A discrete flower pollination-genetic algorithm (DFP-GA) was explored to plan the spindle assembly sequence, presenting the rules for generating the initial population, designing a mechanism of dynamically adjusting the conversion probability, and incorporating a crossover-mutation operation of the genetic algorithm. These modifications have effectively addressed the problem of local optimal solutions, making the algorithm suitable for discrete optimization issues. Finally, this study conducted a comparative experiment of different algorithms using a simplified spindle. DFP-GA demonstrated a probability of obtaining the optimal sequence of up to 83%, exceeding other algorithms by 35%, 6%, and 31% respectively. It also exhibited significantly faster convergence speed, confirming its superiority in solving the ASP problem. This algorithm can enhance production efficiency and reduce manufacturing costs of spindles.