基于广义信息熵测度的制造过程质量评估

Effectiveness Evaluation of Manufacturing Process Quality by Measurement of Extended Information Entropy

制造过程的复杂性导致过程建模、预测和控制难度增大。从信息论的角度看,过程的信息熵与其有序程度成反比关系,因而可以通过信息熵来描述过程的复杂度,进而分析过程的质量状态和演化方向。为定量描述制造过程中的复杂性现象,对信息熵理论进行扩展,建立基于规模、难度和状态多样性的广义信息熵模型。然后按照复杂性对时间的依赖关系,将制造过程的复杂性分解为静态复杂性和动态复杂性,研究利用广义信息熵模型测度制造过程复杂性的方法,并将其用于制造过程质量评估,从复杂性的角度给出过程质量控制有效性的定量分析和评价方法。最后通过实例证明理论和方法的有效性。

The complexity of manufacturing processes causes difficulties in process modeling, forecasting and control. From the information theory point of view, the information entropy of process is inversely related to their degree of order, therefore, process complexity can be described by information entropy to further analyze quality state and evolution direction of processes. To describe quantitatively the complexity in manufacturing processes, the information entropy theory was extended to establish a generalized information entropy model based on size, difficulty and state- diversity. Then complexity of manufacturing processes were divided into static and dynamic complexity based on their dependency on time. The extended information entropy model was used to study how to measure the complexity in manufacturing processes, and the method was applied in quality analyses and evaluation of manufacturing processes to measure quantitatively the effectiveness of process quality control by complexity. Finally, an example demonstrates validity of the proposed theory and methodology.