基于粗糙聚类的航空制造企业零件生产周期分析

摘要

Usually, production cycle time for air plane parts has a significant fluctuation. Thus, it is omportant to accurately estimate such a cycle time. To do so, an advanced k-means clustering algorithm based on rough set theory is proposed for cycle time analysis. With the proposed algorithm, the actual samples are clustered with respect to production cycle time by using upper approximation, lower approximation , and overlapping relationship between clusters. Simulation results for practical instances indicate that the cycle time obtaied by the proposed algorithm is useful for production scheduling and capacity planning.%航空制造企业的零件生产周期波动较大,将基于粗糙集理论的k-means聚类应用于零件生产周期研究,通过周期类上、下近似方法刻画企业实际生产周期样本的归属,并将不同类别的周期表达为一种覆盖关系；实例仿真结果表明该算法能为企业制定期量标准、均衡生产提供决策依据.