机械加工中加工误差产生原因及解决措施

在我国的机械行业中,机械加工是一项非常重要的工作内容,机械加工的质量在很大程度上反映着机械行业的加工质量以及发展前景,因此在我国的机械行业中,对于机械加工还是非常重视,正在不断地加大力度提升机械加工的质量以及机械加工的发展前景。但是在机械加工中不能够忽视的一个主要问题就是机械加工过程中存在的加工误差问题,加工误差的存在在很大程度上能够对机械加工质量以及机械加工的后期使用造成严重的影响。因此本文主要针对机械加工过程中的机械加工误差进行详细的阐述以及分析,希望通过本文的阐述以及分析能够有效地降低机械加工过程中的加工误差的产生,最大限度地提升机械加工准确性以及加工的质量。     

装备制造业关于机械加工精度的探讨

机械加工质量包含机械加工精度和表面质量两部分,加工精度包括三方面内容,具体为尺寸精度、形状精度、位置精度。影响机械加工精度的因素有很多,本文简要叙述了机械加工生产过程及工艺原理,主要对机械加工过程中所产生的误差原因进行分析,并提出了一些提高机械加工精度的方法。     

对机械加工技术质量进行分析

工业作为传统三大产业的成员之一，随着科技的进步，也获得了长足的发展。随着机械加工工艺的Ft趋完善，机械加工质量也不断得到提高。但是，在实际生产活动中，各种工艺系统还是存在一定的原始误差，使得机械加工质量存在问题。比如机床、夹具、刀具的制造误差及磨损、工件的装夹误差、测量误差、工艺系统的调整误差以及加工中的各种力和热所引起的误差等。本文通过对机械加工精度的概念和内容出发，总结机械加工应该遵循的原则，总结机械加工过程中的误差，以及提高机械加工质量的措施和技术。     

试论机械加工质量技术控制

在机械加工中,总存在一定的加工误差。本文就机械加工的质量影响,机械加工产生误差主要原因进行探究分析,从而提出提高加工精度的工艺措施:减少原始误差;误差补偿法;误差抵消法;分化或均化原始误差等,能有效提高机加工的质量。     

试探究机械加工工艺对加工精度的影响

机械加工质量以加工精度作判断,精度即加工后的零件几何形状、尺寸、相互位置及与设计参数的结合程度。机械加工精度受许多因素影响,本文主要从机械加工工艺层面做精度影响分析,通常来说,加工精度受机械加工工艺的影响有:工艺系统热变形、工艺受力变形与工艺几何误差。     

机械加工精度的影响因素和提高措施探析

在机械加工过程中,误差的存在虽是必然的,但是可以将误差控制在允许的范围内。本文从机械加工精度概述入手,在分析机械加工精度影响因素的基础上,对机械加工精度提高措施进行了相应的分析,以减少加工误差,提高加工精度。     

面向加工误差分析的集成CAD/CAE系统

本文在现有的CAD软件Pro／E和有限元分析软件ANSYS基础上，运用二次开发工具ProToolkit和APDL以及编程工具VC 6．0实现零件加工误差分析模块与CAD系统集成，用于分析壳体类零件的平面铣削工序和镗孔工序的加工误差。     

浅析机械加工中质量问题

机械加工产品的质量主要受零件的加工质量和产品的装配质量的影响最为关键,零件加工质量是保障机械加工产品质量的前提,制约零件加工质量的因素有加工精度和表面质量两方面内容。现分析了机械加工精度的基本内容、工艺系统中的加工原理误差和机床的几何误差。通过这些影响机械质量的问题进行分析,对提高机械加工质量提供参考依据。     

对机械加工质量控制进行分析

在机械加工中，总存在一定的加工误差。本文就机械加工的质量影响，机械加工产生误差主要原因进行探究分析，从而提出提高加工精度的工艺措施：减少原始误差；误差补偿法；误差抵消法；分化或均化原始误差等，能有效提高机加工的质量。     

进给系统刚度对内球面车削的误差影响研究

针对目前半闭环车床加工内球面精度低、误差大的现状,研究进给系统刚度对加工误差的影响并提高内球面的加工精度.利用赫兹接触理论对进给系统刚度进行分析,建立了刚度的数学模型．分析了半闭环车床加工内球面的工艺过程,并推导了切削曲面过程中进给系统受力状况,给出了误差表达式．通过对加工误差模型的仿真研究,结果表明进给系统刚度所产生的加工误差与刀位点和母线圆弧形状有关,所产生的误差可通过增发运动脉冲补偿．提出了一种引进补偿机制的插补运算方法,为提高内球面加工精度提供了理论上的指导．     

The Total Source Error of Adjustment model: A methodology for the elimination of setup and process adjustment

The Total Source Error of Adjustment (TSEA) model identifies and describes the sources of error that create the need for setup and process adjustment. Adjustment is the result of uncontrolled sources of variation or error. To control error, it must first be systematically identified and described. The TSEA model is a systematic means of identifying and classifying the error sources contributing to setup adjustment and process adjustment for machining processes. Once error sources are properly classified, touch-trigger probing can then be effectively used to eliminate variability. When implementing the TSEA model, probing is applied to control error sources of adjustment. A case study examines the utility of the TSEA methodology in identifying the sources of variation causing adjustment. The analysis and control of error sources that occur in machining will reduce setup time, increase consistency in manufacturing, and improve the quality of the final product.     

Integrating GD&T into dimensional variation models for multistage machining processes

Recently, the modelling of variation propagation in multistage machining processes has drawn significant attention. In most of the recently developed variation propagation models, the dimensional variation is determined through kinematic analysis of the relationships among error sources and dimensional quality of the product, represented by homogeneous transformations of the actual location of a product's features from their nominal locations. In design and manufacturing, however, the dimensional quality is often evaluated using Geometric Dimensioning and Tolerancing (GD&T) standards. The method developed in this paper translates the GD&T characteristic of the features into a homogeneous transformation representation that can be integrated in existing variation propagation models for machining processes. A mathematical representation using homogeneous transformation matrices is developed for position, orientation and form characteristics as defined in ANSI Y14.5; further, a numerical case study is conducted to validate the developed methods.     

Ensemble modelling technique for a micro-drilling process based on a two-stage bootstrap

Quality improvement in micro-manufacturing processes relies on empirical models. However, if an estimated model varies from the true model because of random errors in experiments, the resulting operating conditions may be located far from the true optimal operating conditions. Using the Pareto chart, which highlights the most important among a set of factors, this article develops a novel ensemble modelling technique which considers the model selection via bootstrap methods. In addition, an integrative optimization strategy is proposed based on interval-data theory, in which the squared bias and the reliability of operating conditions are incorporated into a single framework of a strategy. The proposed method is illustrated with a micro-drilling process, which clearly shows how useful and effective the proposed method is. Through comparative studies, it is also shown that the proposed method has a good robustness property and it provides a reliable scheme for optimizing the machining parameters.     

A new active error compensatory method of machinery accuracy†

A new active error compensatory method for on-line cutting control has been developed for reduction of the form errors in machining. This approach is a combination of in-process gauging and model active compensatory control. In this approach, there are two features of substantial importance: stochastic modelling and optimum forecasting. Through stochastic modelling, the cutting tool error motions can be represented by a simple model without the necessity of obtaining the complex cause-and-effect relationships between various errors and error sources, and more importantly, it is possible to account for both repeatable and non-repeatable parts of errors. Optimum forecasting is an important prerequisite for a rational control strategy, considering the inevitable time delay associate with sensing, computation and actuation. The proposed control method was implemented for the control of cylindricity in boring operations. Through the controller simulation based on experimental measurements, the improvement in cylindricity accuracy confirms the effectiveness of this proposed strategy     

Prediction of toolpath redundancy for NC machining of free-form surfaces based on automatic recognition of steep-wall features

The degree of toolpath redundancy is a critical concern when looking for an appropriate toolpath strategy for free-form surface machining. Hence, quantitative analysis of toolpath redundancy is important to CAM applications. In this work, a novel approach for prediction of toolpath redundancy for free-form surface machining is proposed. Firstly, a general mathematical model to represent toolpath redundancy rate is proposed based on the analysis of local toolpath intervals and their difference from the optimal values. And then, taking the most widely used iso-planar machining as case study, the steep-wall features that bring in the variation of surface slope rates alone machining strips are identified as the main cause of the generation of toolpath redundancy, so a method to automatic recognising steep-wall features from free-form surface is developed. At last, based on the steep-wall feature segmentation, an algorithm is presented to quantitatively predict the toolpath redundancy rate for free-form surface machining. A comparison study is made between the predicted redundancy rates and the experimental results by a number of case studies. The results have validated that the proposed approach can effectively predict the redundancy rate for a surface machining case before the real toolpaths to be generated.     

Modelling and compensation of fixture locators’ error in CNC milling

Fixture errors are one of the error sources in machining operations. The fixture errors consist of positioning inaccuracies and errors due to workpiece and fixture deformations. Fixture locators’ height error causes incorrect positioning of the workpiece in the fixture and inaccuracy in machined surfaces which can be much more than the locators’ height error. For machining precise workpieces, it is necessary to eliminate these errors. This paper presents a method for modelling and compensating the fixture locators’ height error effect on workpiece machined surfaces. In this method, the planes of workpiece actual coordinate system (ACS) are mathematically modelled in the workpiece theoretical coordinate system (TCS). Using the model, required homogenous transformation matrix for coinciding ACS with TCS and modifying machining toolpath for compensating the errors is generated. The presented model is used to develop a post-processing fixture locator error compensation module, which can modify CNC machining codes to eliminate the effect of fixture locators’ height error on the workpiece machined surfaces. For verifying the presented method, machining simulations and cutting experiments have been performed in this work. The results show that the method can eliminate the effect of fixture locators’ height error on the workpiece machined surfaces considerably.     

超精密加工振动误差源诊断实验研究

超精密车床结构及加工过程的复杂性使得对加工精度的影响因素不能完全确定，尤其是随机性因素的影响更难确定。为此本文首先系统分析了超精密车床中影响加工精度的各项误差源，然后通过实验辨识了主要振动误差源对加工精度的影响，为减少和补偿由这些误差源引起的误差提供了依据和指导。     

The Measuring Process

This paper deals with the theory of a proposed method for the statistical study of measuring processes. The practical aspects of the method, including computational details, are discussed in a companion paper published in the ASTM Bulletin. In the present article a theoretical framework is proposed for the mathematical expression of the sources of variation in measuring methods and a suitable method of statistical analysis is described. Particular attention is given, both here and in the companion paper, to interlaboratory studies of test methods. An illustration based on data taken from the chemical literature is appended.     

A Review of Cognitive Models in Human Reliability Analysis

Human error behavior is determined by both environmental and human factors. In particular, psychological and spiritual factors have a decisive impact on human errors. The human cognitive model not only makes a sound exposition of the generation process and mechanism of human erroneous actions but also improves the accuracy and credibility of human reliability analysis (HRA). Therefore, it helps effectively avoid and prevent human errors in industrial fields. This paper highlights the significant role that the cognitive model has played in HRA. Then, based on an analysis of the nature of human behavior and the classifications of common human errors, several typical cognitive models are summarized in the areas of ergonomics, behavioral science, and cognitive engineering, including a cognitive model related to process, an information‐processing model, a decision‐making and problem‐solving process model, and a cognitive simulation model based on computer technology. Then, cognitive models and the corresponding HRA methods that are applied in the fields of reliability engineering, safety engineering, and risk assessment are reviewed. Finally, some directions and challenges are proposed for the future research of cognitive models applied in HRA methods based on the discussion of current cognitive models used in HRA methods. Copyright © 2016 John Wiley & Sons, Ltd.