基于AHP-信息熵的数控机床精度指标体系构建与验证

Construction and verification of precision indicator system for CNC machine tools based on AHP-information entropy

  • 摘要: 针对高端数控机床精度评价中指标冗余、权重确定主观性强的问题,提出一种融合层次分析法(analytic hierarchy process, AHP)与信息熵的组合赋权与关键指标筛选方法。首先,系统汇总了涵盖几何、位置、加工与运动精度的多层次指标库;其次,综合基于专家经验的AHP权重与基于实测数据的信息熵权重进行组合赋权,并引入帕累托定律,依据累计贡献度筛选出累计权重占比约80%的关键指标,从而形成结构精简、重点突出的最终评价体系。应用该体系对5台不同类型的机床进行评价,其综合得分与指标强弱项分布符合工程认知,验证了体系的有效性与实用性。该方法为机床精度的系统性评价与质量分级提供了可操作的理论工具。

     

    Abstract: To address the issues of indicator redundancy and the subjective nature of weight determination in the accuracy evaluation of high-end CNC machine tools, this study proposes a combined weighting and key indicator screening method that integrates the analytic hierarchy process (AHP) with information entropy. Firstly, a multi-level indicator library covering geometric, positional, machining, and motion accuracies was systematically compiled. Secondly, a combined weighting approach was developed by integrating AHP weights derived from expert experience with entropy weighting based on empirical measurement data. By applying the Pareto principle, key indicators accounting for approximately 80% of the cumulative weight were selected based on their cumulative contribution, thereby forming a streamlined evaluation system that highlights critical aspects. When applied to evaluate five machine tools of different types, the comprehensive scores and the distribution of indicator strengths and weaknesses aligned with engineering expectations, validating the system’s effectiveness and practicality. This method provides a practical theoretical tool for the systematic evaluation and quality classification of machine tool accuracy.

     

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