金属切削毛刺的预测预报技术研究

系统概括了国内外时金属切削毛刺的预报预测研究现状,分析了有限元法在毛刺形成过程、形态度尺寸大小和界限转换条件的定量或定性预测预报中的具体应用,为系统深入地研究切削毛刺提供了理论基础.     

金属切削毛刺预报研究现状分析

阐述了金属切削毛刺形成预报研究的背景,并国内外学者的研究现状进行了分析研究,并且做出了比较,再在总结与归纳出金属切削毛刺预报的研究现状中尚存在的一些问题的基础上,指出在科技不断发展的现在,对金属切削加工技术的要求也越来越高,由于金属切削毛刺研究说涉及的领域很多,所以也给研究带了了新的机遇与挑战。最后指出了解决金属切削毛刺形成预报的关键问题和研究的发展方向。     

金属切削毛刺专家知识系统的开发

毛刺是金属切削加工中产生的常见现象。研究开发出了金属切削毛刺专家知识系统，为管理切削实验所测的毛刺数据、查询毛刺类型与尺寸、优化选择加工参数和进行切削毛刺形成的动力学仿真等奠定了基础。进而，为实现切削毛刺的预报与控制开辟了新途径。     

金属切削毛刺数据库系统的设计

毛刺的产生和存在是金属切削加工中普遍存在的问题 ,它直接影响了工件的加工精度及质量。基于数据库和Java ,研究了金属切削毛刺数据库系统的设计 ,实现了切削毛刺数据的管理、切削毛刺类型与尺寸大小及加工参数的查询 ,进一步丰富和完善了金属切削毛刺的预报与控制理论。     

微细切削毛刺发展研究

微细切削加工中形成的毛刺严重降低了被加工微型零部件的精度和棱边质量,影响了工件的使用性能,对微细切削的毛刺研究有利于推动微细切削技术的发展。系统概述了国内外微细切削毛刺的研究进展,重点阐述了研究者对微细切削毛刺形成机理、影响因素及预测预报技术的研究,并在分析微细切削特殊切削环境的基础上,结合尺度效应理论研究了微细切削毛刺的形成机理,指出了微细切削毛刺研究尚存的主要问题,同时确立了今后深入开展微细切削毛刺研究的发展方向。     

基于神经网络的金属切削毛刺专家系统的研究及应用

机械加工中毛刺的形成与存在影响、制约着精密与超精密加工和自动化加工技术的发展。基于神经网络理论,构建并开发了金属切削毛刺专家系统(Ujs),通过对神经网络的设计,并作为推理机制,以数据库为训练样本,建立了毛刺形态、尺寸与切削条件之间的映射模型,应用于金属切削毛刺的控制及预报。结合车削实验,比较了系统预报结果与实验结果,取得了较好的吻合。神经网络专家系统的建立为解决毛刺预报与控制提供了一条有效的途径。     

金属切削毛刺形成与控制技术研究进展

本文系统概述了国内外对于毛刺形成机理及控制技术的研究进展,重点阐述了预测毛刺形成的解析模型和有限元模型、毛刺形成过程的实验研究以及控制毛刺形成的加工工艺和非标刀具,分析了亟待解决的问题,指出了金属切削毛刺形成机理和控制技术研究的方向.     

基于毛刺的切削参数优化试验研究

金属切削中的毛刺是切削加工中产生的常见现象,它严重地影响产品的精度和使用性,有必要对毛刺的预测进行深入的研究。本文针对铣槽时产生的出口毛刺高度进行试验与检测,并通过田口直交表进行统计分析,对检测到的试验数据运用相关公式进一步进行计算优化,然后根据传统的经验值与优化计算的数据进行比较,获取了以毛刺高度为控制对象的切削用量优化值,以此为依据提出在加工过程中夹具、机床等相关的数据优化,为进一步对毛刺控制的非线性数学模型的建立提供试验数据。     

金属切削毛刺生成机理的研究及其发展

对国内外金属切削毛刺生成机理的研究沿革及现状进行系统的概述与分析，指出金属切削毛刺研究中尚待解决的主要问题及其发展前景。     

少无毛刺切削技术的研究进展

在系统概述国内外少无毛刺切削加工技术研究进展的基础上,根据机械加工实际需要,给出了主动控制或减小金属切削毛刺的基本原则,探索出少无毛刺的主要途径。此外,分析了几种切削加工技术的具体应用。指出了目前尚需解决的一些主要问题,确立了今后深入开展金属切削毛刺研究的方向。     

FORMING PRINCIPLE OF TWO SIDE-DIRECTION BURR AND IT‘S PREDICTION IN METAL CUTTING

OgyAbethect The burr is one of the common phenomena occutring in metal cutting OPerations. The mat hematical- mechaniedmodel of two side-direction burr fOrmation and transformation is established with plane stress-strain thcory, based on theorthogonal cutting. The main laws of fOrmation and change of the burr are revealed, and it is confirmed by expedmentresult, which first realizes prediction of the forming and changing of the two sidesdirection burr in metal cutting operation.Key wOrds:Me…     

Characterization and modeling of burr formation in micro-end milling

Mechanical micromachining is increasingly finding applications in fabrication of components in various fields, such as, biomedical devices, optics, electronics, medicine, communications and avionics. In order to ensure adequate functionality, there are stringent requirements for form and finish in case of biomedical devices like cochlear implants and metallic optics. This necessitates that the post machined surface must be burr free. To address these issues in micromachining, this paper presents results of an experimental study to investigate the influence of main process parameters i.e. speed, feed rate, depth of cut, tool diameter and number of flutes on the formation of the various types of burrs i.e. exit burrs and top burrs produced during micro-end milling operation. The experiments performed using Taguchi method shows that three types of burr formation mechanisms prevail during micro-end milling operations; these are: lateral deformation of material, bending and tearing of the chip. Also, three types of burrs were observed include: Poisson burr, rollover burr in down milling and tear burr in up milling. Further, it is observed that the depth of cut and the tool diameter are the main parameters, which influence the burr height and thickness significantly. However, the speed and the feed rate have small to negligible effect on the burr thickness and height. Besides the experimental analysis, the paper presents an analytical model to predict the burr height for exit burr. The model is built on the geometry of burr formation and the principle of continuity of work at the transition from chip formation to burr formation. Note that prediction of burr height in micro-end milling is extremely challenging due to the complex geometry of material removal and microstructural effects encountered during cutting at that length scales. The model fares well and the prediction errors range between 0.65 and 25%.     

Prediction of burr formation during face milling using a hybrid GMDH network model with optimized cutting conditions

In this paper, a combined hybrid group method for data handling and optimization approach is introduced to predict burr types formed during face milling. The hybrid group method for data handling (hybrid GMDH) network was constructed for realizing predictive models for the machining of aluminum alloy, and differential evolution was selected for the optimization of burr formation problem resulting in finding optimal parameter for minimizing burr formation. Burr type was included as a parameter resulting in a classification scheme in which the burr type becomes the group label and it is therefore possible in the future to classify a machining process into any of these burr types. The resulting hybrid GMDH output was in agreement with experimental results, thereby validating the proposed scheme for modeling and prediction of burr formation in milling operations.     

Modeling of burr thickness in milling of ductile materials

Accuracy and surface finish play an important role in modern industry. The presence of undesired projections of materials, known as burrs, negatively affect the part quality and assembly process. To remove burrs, a secondary operation known as deburring is required for the post-processing and edge finishing of machined parts. The thickness of the burr is of interest as it describes the time and method necessary for deburring of the machined part. Burr thickness (B _t) measurements are costly and non-value-added operations that in most cases require the use of a scanning electron microscope for accurate burr characterization. Therefore, to avoid such expenses, the implementation of alternative methods for predicting the burr thickness is strongly recommended. In this research work, an analytical model for predicting the burr thickness in end milling of ductile materials is presented. The model is built on the geometry of burr formation and the principle of continuity of work at the transition from chip formation to burr formation that also takes into account the cutting force influence on burr formation. A very good correlation was found between the modeled and experimental B _t values. The model has shown a great sensitivity to material properties such as yield strength and specific cutting force coefficient (K _c). In addition, the sensitivity of the proposed model to the feed per tooth (f _t) and depth of cut (a _p) was considerably high. The proposed model allows the prediction of the thickness of the exit up milling side burr, without the need for experimental measurement and/or approximation of shear angle (Φ), friction angle (λ), and the tool chip contact length (L), unlike existing analytical burr size prediction models. Besides analytical modeling, statistical analysis is performed on experimental results in order to distinguish dominant process parameters on B _t. It is observed that the depth of cut and feed per tooth are the main parameters which significantly affect the B _t, while the speed has only a negligible effect on it.     

Development of a micro-drilling burr-control chart for PCB drilling

A drilling burr-control chart (DBCC), based on experimental results, is a tool for the prediction and control of drilling burrs for a large range of drilling parameters. A micro-drilling burr-control chart (M-DBCC) was developed for a standard double-sided copper-clad laminated (CCL) printed circuit board (PCB) with laminated fiber-reinforced plastic (FRP) substrate. This chart will assist in the selection of favorable drilling parameters for predicting and achieving preferred types of burrs. Burr classification was carried out according to the burr geometric characteristics, burr formation mechanisms, burr height, and drill bit breakage while drilling. The design of experiment (DOE) technique based on the Taguchi method was used to find the most significant drilling parameter affecting burr height. The results show that the drill diameter makes a statistically significant contribution to burr-height variation.     

FINITE ELEMENT MODELING OF BURR FORMATION IN ORTHOGONAL CUTTING

A finite element model for orthogonal cutting is developed and applied to simulate burr formation. Three typical workpiece materials were investigated. The simulation results reveal the entire burr formation process. The simulation produces either positive or negative burrs depending on the material properties, which is in agreement with experimental observations from literature. Both shear and normal stress failures are presented for negative burr formation while only shear stress failure leads to positive burr formation. The FE modeling results confirm that material property is the dominant factor in controlling burr formation.     

Development of intelligent system to minimize burr formation in face milling

The exit burr generated in the face milling operation at the edge of the workpiece usually requires deburring processes to enhance the level of precision of the parts. This paper is to geometrically understand the formation of the exit burr in the face milling operation on the arbitrary shaped workpiece with multiple feature such as hole, spline, and arc so that we can suggest the cutting conditions and tool path to minimize the burr formation on the given workpiece in the early design stage. The burr formation mechanism in each type of burr is classified based on the experimental results. A database is developed to store and predict burr formation results. A Windows based program is developed with the algorithm including three steps, i.e., the feature identification, the cutting condition identification, and the analysis on exit burr formation. We can predict which portion of the workpiece would have the exit burr in advance so that we can manage to find a way to minimize the exit burr formation in an actual cutting. Here, the idea of critical burr length is introduced as a criterion in optimization.