面向动作层的三维质量屋优化模型

为解决数控机床多关键质量特性的复杂控制问题,以元动作理论为基础,对传统的二维质量屋(House of Quality,HOQ)进行拓展,建立一种基于影响因素维、元动作单元维以及关键质量特性维的三维质量屋(Three-dimensional House of Quality,THOQ)优化模型.采用蚁群聚类算法(Ant Colony Clustering Algorithms,ACCA)对动作层关键质量特性的影响因素进行筛选,并结合证据推理递归理论(Evidence Reasoning Recursive Theory,ERRT)建立了影响因素自相关矩阵、各个元动作单元关键质量特性与影响因素之间的关联矩阵和元动作单元性能耦合矩阵,基于质量控制成本约束和开发时间约束建立以关键质量特性波动度为目标函数的优化模型,优化得到影响因素的最优值,使动作层关键质量特性波动值最小.以某数控机床的分度转台运动为例进行优化,并通过实验对比验证了该模型的合理性和有效性.

Optimization model of three-dimensional house of quality for action layer

To solve the complex control problems of multiple key quality characteristics of NC machine tools, based on meta-action theory and two-dimensional House of Quality(HOQ), a three-dimensional House of Quality (THOQ) model with the influencing factors dimension, the meta-action units dimension and the key quality characteristics dimension was established. The action layer factors affecting the key quality characteristics were screened by Ant Colony Clustering Algorithm, and combined with Evidence Reasoning Recursive Theory(ERRT), the autocorrelation matrix of the factors, the correlation matrix between the key quality characteristics and the influencing factors of each meta action unit and performance coupling matrix of meta-action units were established. Based on quality control cost constraint and development time constraint, an optimization model with key quality characteristics fluctuation degree as objective function was established, and the optimal value of the influencing factors were obtained, so that the fluctuation value of the key quality characteristics was minimized. Finally, an example was given to optimize the indexing table motion of a NC machine tool, and the rationality and validity of the model were verified by experiments.