复杂零件加工过程质量控制理论与方法研究
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摘要
复杂零件是指结构复杂、多质量特征、多加工工序、高制造精度的机械零件,其加工过程的质量控制是提高产品质量和企业竞争力的基础。本文以复杂零件加工过程质量控制为对象,采用理论分析与工程应用相结合的研究方法,重点研究复杂零件加工过程误差传递建模、误差源可诊断性分析和识别、加工过程工艺能力指数计算及调控、加工过程装夹规划选择等核心技术,构建复杂零件加工过程质量控制的理论基础,提出面向装配的复杂零件加工过程质量控制方法。论文的主要研究内容如下：
(1)在分析复杂零件加工过程特征和误差源的基础上,提出复杂零件加工过程误差传递的状态空间建模理论。采用微分运动矢量描述工件,采用齐次变换建立复杂零件加工过程误差传递模型,确立复杂零件加工质量特征误差与加工过程中各种过程参数之间明确的数学关系,实现复杂零件加工过程误差传递的量化分析,并用实例加以验证。
(2)复杂零件加工过程误差信息传递和误差源识别问题研究。在分析复杂零件加工过程误差信息相关性的基础上,提出一种误差源的在线识别方法。通过把误差传递模型转化成线性混合形式,建立加工过程误差源的识别模型；参考线性混合模型中可识别性的概念,建立复杂零件加工过程误差源的完全可诊断模型和部分可诊断模型,提出部分可诊断加工过程的最小可诊断类和可诊断性分析方法；将多元方差成分分析方法引入到加工过程诊断中,结合工程实例,提出基于参数估计和检验统计的复杂零件加工过程误差源在线识别方法,实现加工过程误差源的快速识别。
(3)复杂零件加工过程工艺能力问题研究。在研究复杂零件加工过程调整策略的基础上,建立复杂零件加工过程工艺能力的观察模型；采用田口质量损失函数,提出复杂零件加工过程的工艺能力指数的计算方法；为获得效能最优的过程工艺能力调控方法,提出两层的复杂零件加工过程工艺能力影响参数的敏感性分析模型,以此确定过程调整的方向和方位；结合工程实例,提出复杂零件加工过程工艺能力调控方法。
(4)复杂零件加工过程装夹规划优化问题研究。基于复杂零件加工过程误差传递模型,建立复杂零件加工装夹误差传递模型和以满足质量规范且加工成本最小为目标函数的装夹规划优化模型,并采用动态规划理论求解,实现复杂零件加工装夹工艺参数的优化配置。
(5)面向装配的复杂零件加工过程质量控制问题研究。在分析面向装配的复杂零件加工过程质量控制问题的基础上,提炼出其核心技术,提出装配中选配度的计算公式；在研究单个复杂零件加工过程质量控制流程的基础上,提出面向装配的复杂零件加工过程质量控制流程；结合工程实例,提出面向装配的复杂零件加工过程质量控制方法。
A complex workpiece is defined as a kind of mechanical part which has complex composition, multiple quality characteristics, multiple machining processes, and high manufacturing precise. The quality control of complex workpiece machining process (CWMP) is the basis of product quality improvement and the competitive ability of enterprises. The CWMP quality control is concerned in this dissertation, the research method of this dissertation is combining the theory analysis with practice application. The core technologies, such as machining process variation propagation modeling, variation sources diagnosability analysis and identification, machining process technology capability index calculation and improvement, setup planning selection in machining process, etc., have been mainly studied. The basis of the CWMP quality control theory is established. A CWMP quality control method for assembly is proposed. The main contributions of this dissertation are as follows.
(1) On the basis of the CWMP characteristic and variation sources analysis, a CWMP variation propagation modeling theory based on state space model is proposed. A machining variation propagation model is established by describing the workpiece with the differential motion vector according to the kinematic principle. This model explicitly describes the relationship between quality characteristic variations of CPMP and their variation sources, which can quantify the variation propagation effects analysis among different stages and is testified by an example.
(2) To study the quality variation information propagation and identify the variation sources in the CWMP, a variation sources on-line identification method is proposed based on the complicate mutuality analysis of quality variation information in the CWMP. An identification model for the CWMP variation source is established by translating the variation propagation model into a linear mixed model. A variation source fully diagnosable model and a partially diagnosable model are presented for the CWMP by referring to the identifiability in a linear mixed model. To study the partially diagnosable CWMP, the concept of a minimal diagnosable class is proposed to identify the process variation and realize the identifiability study of partially diagnosable process. On this basis, introducing the multivariate variance components analysis method into the CWMP diagnosis, combining an engineering case, an on-line variation sources identification method for CWMP is proposed based on statistical estimates and hypothesis testing, which realizes the quick variations sources identification in the CWMP.
(3) To study the problem of the process technology capability in the CWMP, an observation model is established for technology capability in the CWMP according to the process adjustment strategy, a technology capability index measuring method is presented based on Taguchi's quality loss function. Based on this, in order to achieve the highest efficiency method of process technology capability adjustment, a two-level sensitive analysis model for process technology capability impact parameter model is proposed to determine the positions and directions of the process adjustment. A technology capability adjustment method for the CWMP is proposed by combining an engineering case.
(4) To study the optimization of setup planning in the CWMP, a setup variation propagation model is established based on the variation propagation model of the CWMP. A minimum cost and quality assured function is defined for an objective function to obtain an optimal setup planning selective decision and the solution of this problem is based on dynamic planning algorithm, which realizes the optimum configuration of setup planning parameters in the CWMP.
(5) To study the CWMP quality control method for assembly, the core technologies are extracted according to the analysis of CWMP quality control problem for assembly, a matchable degree calculation formula is proposed. The CWMP quality control flow for the assembly is presented based on the study of the CWMP quality control flow for the single. A CWMP quality control method for assembly is presented by combining an engineering case.
(1)在分析复杂零件加工过程特征和误差源的基础上,提出复杂零件加工过程误差传递的状态空间建模理论。采用微分运动矢量描述工件,采用齐次变换建立复杂零件加工过程误差传递模型,确立复杂零件加工质量特征误差与加工过程中各种过程参数之间明确的数学关系,实现复杂零件加工过程误差传递的量化分析,并用实例加以验证。
(2)复杂零件加工过程误差信息传递和误差源识别问题研究。在分析复杂零件加工过程误差信息相关性的基础上,提出一种误差源的在线识别方法。通过把误差传递模型转化成线性混合形式,建立加工过程误差源的识别模型；参考线性混合模型中可识别性的概念,建立复杂零件加工过程误差源的完全可诊断模型和部分可诊断模型,提出部分可诊断加工过程的最小可诊断类和可诊断性分析方法；将多元方差成分分析方法引入到加工过程诊断中,结合工程实例,提出基于参数估计和检验统计的复杂零件加工过程误差源在线识别方法,实现加工过程误差源的快速识别。
(3)复杂零件加工过程工艺能力问题研究。在研究复杂零件加工过程调整策略的基础上,建立复杂零件加工过程工艺能力的观察模型；采用田口质量损失函数,提出复杂零件加工过程的工艺能力指数的计算方法；为获得效能最优的过程工艺能力调控方法,提出两层的复杂零件加工过程工艺能力影响参数的敏感性分析模型,以此确定过程调整的方向和方位；结合工程实例,提出复杂零件加工过程工艺能力调控方法。
(4)复杂零件加工过程装夹规划优化问题研究。基于复杂零件加工过程误差传递模型,建立复杂零件加工装夹误差传递模型和以满足质量规范且加工成本最小为目标函数的装夹规划优化模型,并采用动态规划理论求解,实现复杂零件加工装夹工艺参数的优化配置。
(5)面向装配的复杂零件加工过程质量控制问题研究。在分析面向装配的复杂零件加工过程质量控制问题的基础上,提炼出其核心技术,提出装配中选配度的计算公式；在研究单个复杂零件加工过程质量控制流程的基础上,提出面向装配的复杂零件加工过程质量控制流程；结合工程实例,提出面向装配的复杂零件加工过程质量控制方法。
A complex workpiece is defined as a kind of mechanical part which has complex composition, multiple quality characteristics, multiple machining processes, and high manufacturing precise. The quality control of complex workpiece machining process (CWMP) is the basis of product quality improvement and the competitive ability of enterprises. The CWMP quality control is concerned in this dissertation, the research method of this dissertation is combining the theory analysis with practice application. The core technologies, such as machining process variation propagation modeling, variation sources diagnosability analysis and identification, machining process technology capability index calculation and improvement, setup planning selection in machining process, etc., have been mainly studied. The basis of the CWMP quality control theory is established. A CWMP quality control method for assembly is proposed. The main contributions of this dissertation are as follows.
(1) On the basis of the CWMP characteristic and variation sources analysis, a CWMP variation propagation modeling theory based on state space model is proposed. A machining variation propagation model is established by describing the workpiece with the differential motion vector according to the kinematic principle. This model explicitly describes the relationship between quality characteristic variations of CPMP and their variation sources, which can quantify the variation propagation effects analysis among different stages and is testified by an example.
(2) To study the quality variation information propagation and identify the variation sources in the CWMP, a variation sources on-line identification method is proposed based on the complicate mutuality analysis of quality variation information in the CWMP. An identification model for the CWMP variation source is established by translating the variation propagation model into a linear mixed model. A variation source fully diagnosable model and a partially diagnosable model are presented for the CWMP by referring to the identifiability in a linear mixed model. To study the partially diagnosable CWMP, the concept of a minimal diagnosable class is proposed to identify the process variation and realize the identifiability study of partially diagnosable process. On this basis, introducing the multivariate variance components analysis method into the CWMP diagnosis, combining an engineering case, an on-line variation sources identification method for CWMP is proposed based on statistical estimates and hypothesis testing, which realizes the quick variations sources identification in the CWMP.
(3) To study the problem of the process technology capability in the CWMP, an observation model is established for technology capability in the CWMP according to the process adjustment strategy, a technology capability index measuring method is presented based on Taguchi's quality loss function. Based on this, in order to achieve the highest efficiency method of process technology capability adjustment, a two-level sensitive analysis model for process technology capability impact parameter model is proposed to determine the positions and directions of the process adjustment. A technology capability adjustment method for the CWMP is proposed by combining an engineering case.
(4) To study the optimization of setup planning in the CWMP, a setup variation propagation model is established based on the variation propagation model of the CWMP. A minimum cost and quality assured function is defined for an objective function to obtain an optimal setup planning selective decision and the solution of this problem is based on dynamic planning algorithm, which realizes the optimum configuration of setup planning parameters in the CWMP.
(5) To study the CWMP quality control method for assembly, the core technologies are extracted according to the analysis of CWMP quality control problem for assembly, a matchable degree calculation formula is proposed. The CWMP quality control flow for the assembly is presented based on the study of the CWMP quality control flow for the single. A CWMP quality control method for assembly is presented by combining an engineering case.
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