Optimal design of electrode cooling system for resistance spot welding with the response surface method

In the last decade, the progress of surface metrology has led to improved 3D characterisation of surfaces, offering the possibility of monitoring manufacturing operations and providing highly detailed information regarding the machine tool condition. This paper presents a case study where areal surface characterisation is used to monitor tool wear in peripheral milling. Due to the fact that tool wear has a direct effect on the machined workpiece surface, the machined surface topography contains much information concerning the machining conditions, including the tool wear state. By analysing the often subtle changes in the surface topography, one can highlight the tool wear state. This paper utilises areal surface characterization, areal auto-correlation function (AACF) and pattern analysis to illustrate the effect of tool wear on the workpiece surface. The result shows the following: (1) tool wear, previously difficult to detect, will influence almost all of the areal surface parameters; (2) the pattern features of AACF spectrum can reflect the subtle surface texture variation with increasing tool wear. The authors consider that, combined analysis of the surface roughness and its AACF spectrum are a good choice for monitoring the tool wear state especially with the latest developments in on-machine surface metrology.     

一个应用于自动化加工系统的综合刀具监测系统

对于自动化加工系统、刀具破损和异常磨损的有效实时监测是一个亟待解决的问题。本文用声发射信号监测加工中心上各种刀具的破损、折损,针对多种工序、多咱切削条件的复杂情况,进行了可变参数的模式识别算法的研究。基于这个算法,开发了一个综合刀具破损监测系统。这个系统针对自动化加工基本单元——加工中心的车、镗、铣多种工序,使得自动化加工系统的综合监测成为可能。实验验证表明,识别成功率大于90%。     

TRIBOLOGY ISSUES IN MACHINING

Machining is the process of shaping materials into useful articles by removing the unwanted material. In traditional machining processes such as in cutting and grinding, the unwanted material is removed by mechanical means using a cutting tool. Since the tool makes contact with the workpiece and either the tool, the workpiece, or both are in motion, tribology (i.e., the study of rubbing or sliding) becomes an important issue. Tribology has a crucial and significant role as an enabling technology, since tool wear is a major problem in the production of reliable and cost-effective products. This paper reviews recently published articles related to the wear of cutting tools and grinding wheels. These papers are classified into such areas as the wear process, measurement of wear, reduction of wear through the use of different cutting tools and abrasive materials, strategies used to monitor wear during machining and grinding, and in-process control of machining to compensate for tool wear.     

New tool-workpiece setting up technology for micro-milling

A major issue in micromilling is the setting up with the necessary accuracy the work coordinate system on the machine. The spindle thermal stability during the setting up procedure make this a very difficult task. Thus, it is essential to develop new tool setting up technology to increase the process productivity, reduce machine setting up times and errors, and at the same time improve the precision and quality of machined components. The paper presents a cost-effective and reliable method for setting up the work coordinate system for micro-milling operations employing an on-line tool–workpiece voltage monitoring system. The viability of the proposed method was verified in a series of experiments conducted on an ultra-precision micromilling machine centre. The experimental trials involved the machining of test parts in brass with cutters 100 and 200 µm in diameter. The results of these experiments were analysed and compared with the capabilities of currently available methods and technologies on micro milling machine tools for condition monitoring and setting up the working coordinate systems. Finally, conclusions are made about the effectiveness of the proposed new tool-workpiece setting up technology for micro milling.     

Self-Learning Algorithm for Automated Design of Condition Monitoring Systems for Milling Operations

This paper investigates an approach, termed self-learning ASPS (automated sensor and signal processing selection), aimed at aiding the systematic design of condition monitoring systems for machining operations. The paper outlines a self-learning methodology for the classification of the system’s normal and faulty states and the selection of the most appropriate sensors and signal processing methods for detecting machining faults in end milling. The aim of the proposed approach is to enable the condition monitoring designer to use previous system faults or incidents to design an on-line monitoring system, reducing the system’s development time and cost. Force, acceleration and acoustic emission signals are used to design the condition monitoring systems for end milling operations. Gradual tool wear, catastrophic cutter breakage and tool collision are used for evaluating the proposed self-learning ASPS approach. The initial results show that the suggested algorithm can be applied for an automated, self-learning monitoring system for the selection of the most sensitive sensors and signal processing methods for machining faults and conditions.       

Milling Force Model for Aviation Aluminum Alloy:Academic Insight and Perspective Analysis

Aluminum alloy is the main structural material of aircraft,launch vehicle,spaceship,and space station and is pro-cessed by milling.However,tool wear and vibration are the bottlenecks in the milling process of aviation aluminum alloy.The machining accuracy and surface quality of aluminum alloy milling depend on the cutting parameters,material mechanical properties,machine tools,and other parameters.In particular,milling force is the crucial factor to determine material removal and workpiece surface integrity.However,establishing the prediction model of milling force is important and difficult because milling force is the result of multiparameter coupling of process system.The research progress of cutting force model is reviewed from three modeling methods:empirical model,finite element simulation,and instantaneous milling force model.The problems of cutting force modeling are also determined.In view of these problems,the future work direction is proposed in the following four aspects:(1)high-speed milling is adopted for the thin-walled structure of large aviation with large cutting depth,which easily produces high residual stress.The residual stress should be analyzed under this particular condition.(2)Multiple factors(e.g.,eccentric swing milling parameters,lubrication conditions,tools,tool and workpiece deformation,and size effect)should be consid-ered comprehensively when modeling instantaneous milling forces,especially for micro milling and complex surface machining.(3)The database of milling force model,including the corresponding workpiece materials,working condi-tion,cutting tools(geometric figures and coatings),and other parameters,should be established.(4)The effect of chatter on the prediction accuracy of milling force cannot be ignored in thin-walled workpiece milling.(5)The cutting force of aviation aluminum alloy milling under the condition of minimum quantity lubrication(mql)and nanofluid mql should be predicted.     

Factors affecting chemical wear during machining

Very substantial tool wear may arise during machining processes because of chemical affinities between tool and workpiece. Studies have been made of this type of wear by observing the performance under various conditions of diamond tools turning steel, nickel and graphite, of tungsten tools turning graphite, and of CuNi tools turning sulphur. The reactions involved in the wear processes are insensitive to thermal activation and appear to be due to the reactivity of the atomically clean surfaces generated by the machining. The rates of wear are considerably modified both by changes in the chemical composition of tool and workpiece and by changes in the gaseous environment. It is clear that reactions between solid surfaces are at present not well understood and are worthy of further study. The results suggest possible ways of reducing tool wear both in turning and in other operations.     

Wear characteristics of diamond tool in ultraprecision raster milling

Ultraprecision freeform raster milling is a very complex machining process, and long machining time is used for small components. Therefore, the diamond tool wear is a crucial factor that not only raises the machining cost but also limits the cutting performance in ultraprecision raster milling. In this paper, the methods of process monitoring and wear evaluating of single-crystal diamond tools during the raster milling of copper are studied in two types of cutting environment: with lubrication and without lubrication. Experimental results indicate that the impact and free vibration are important dynamic characteristics in raster milling process that result in the obvious microchipping wear on the cutting edge.     

Investigations on model-based simulation of tool wear with carbide tools in milling operation

This paper deals with tool wear in milling operation using carbide tools. The main purpose of this work is to define a model-based procedure for forecasting tool-wear progression during cutting operation by using machining simulation. Firstly, a multi-axis machining simulation algorithm is proposed based on DEXEL model and local area update method. NC milling machining process simulation software NCToolWearSim is realized by using Visual C++ and OpenGL. The developed process simulation software is used to simulate the cutting process. Secondly, tool-wear simulation algorithm in the machining process is presented with tool-wear model and machining simulation algorithm and is implemented into the machining simulation software NCToolWearSim in order to evaluate the tool wear and to update the tool geometry. The tool-wear value is estimated according to the established tool-wear model from experienced tool-wear data. Thus, tool-wear progression can be visualized in milling operation by using NCToolWearSim. Finally, experimental tests, performed milling integral wheel with carbide tools, were used to calibrate and validate the correctness of tool-wear simulation process based on the tool-wear model.     

A study of tool wear using statistical analysis of metal-cutting acoustic emission

Many aspects of the interactions between cutting tools, workpiece material and the chips formed during machining that affect the wear and failure of the tool are not fully understood. The analysis of acoustic emission signals generated during machining has been proposed as a technique for studying both the fundamentals of the cutting process and tool wear and as a methodology for detecting tool wear and failure on line. A brief review of the theory of acoustic emission is presented. Acoustic emission data from reduced contact length machining experiments and tool flank wear tests are analyzed using distribution moments. The analysis shows that the skew and kurtosis of an assumed β distribution for the r.m.s. acoustic emission signal are sensitive to both the stick-slip transition for chip contact along the tool rake face and progressive tool wear on the flank of the cutting tool.     

Monitoring of hard turning using acoustic emission signal

Monitoring of tool wear during hard turning is essential. Many investigators have analyzed the acoustic emission (AE) signals generated during machining to understand the metal cutting process and for monitoring tool wear and failure. In the current study on hard turning, the skew and kurtosis parameters of the root mean square values of AE signal (AERMS) are used to monitor tool wear. The rubbing between the tool and the workpiece increases as the tool wear crosses a threshold, thereby shifting the mass of AERMS distribution to right, leading to a negative skew. The increased rubbing also led to a high kurtosis value in the AERMS distribution curve.     

Experimental study of high-speed milling of SiCp/Al composites with PCD tools

In this paper, high-speed milling experiments on silicon carbide particle reinforced aluminum matrix (SiCp/Al) composites with higher volume fraction and larger particles were carried out using polycrystalline diamond (PCD) tools at dry and wet machining conditions. For comparison, a TiC-based cermet tool was also used in milling the same workpiece material at very low speed. Worn PCD and cermet tools were measured and extensively characterized by scanning electron microscopy at different machining conditions. Furthermore, the effect of cutting distance on milling force and surface roughness were also investigated. The results showed that the main tool wear mechanism in machining of this type of material was abrasion on the flank face, and it was verified that the TiC-based cermet tool was not suitable for machining SiCp/Al composites with higher volume fraction and larger particles due to the heavy abrasive nature of reinforcement.     

Modelling the effect of flank wear on machining thrust stability

This paper discusses an analytical assessment of the effect of cutting tool flank wear on machining stability along the thrust direction in a turning operation based on an analysis of frequency band root-mean-square (RMS) level of the accelerometer signals. The energy content of machining at the tool-tip/workpiece interface along the flank is represented by the RMS signal level, in comparison to the random vibration of the cantilever portion of the tool holder. The RMS signals measured from a tool-post accelerometer in stable machining with tool wear effect are calculated using the frequency band RMS method at the first natural frequency of the cantilever portion of the tool holder. Increasing flank wear results in increasing stability and decreasing RMS in the thrust direction in machining. For model validation, a series of machining experiments were performed under the condition of various flank wear/land widths, while the RMS signals from a tool-post accelerometer were collected and studied. It was found that theoretical predictions were shown to be in agreement with experimental results.     

An experimental investigation of tool wear in electric discharge machining

In this study, the variations of geometrical tool wear characteristics – namely, edge and front wear – and machining performance outputs – namely, workpiece removal rate, tool wear rate, relative wear and workpiece surface roughness – were investigated with varying machining parameters. Experiments were conducted using steel workpieces and round copper tools with a kerosene dielectric under different dielectric flushing conditions (injection, suction and static), discharge currents and pulse durations. The experiments have shown that machining parameters and dielectric flushing conditions had a large effect on geometric tool wear characteristics and machining performance outputs. Additionally, published research on tool wear is presented in detail in this study.     

Wear maps for some uncoated cutting tools

The method of using maps and diagrams to present wear rates and wear mechanisms, as well as showing the relationships between them, has been applied to cutting tools. In this summary paper, wear maps obtained earlier for uncoated high-speed steel (HSS) cutting tools are presented together with maps for uncoated carbide cutting tools. Within the two-dimensional area of a wear map defined by two easily controlled machining parameters, namely feed rate and cutting speed, the rates of tool wear, and the wear mechanisms observed during actual dry turning operations, are displayed. The presence of safety zones and least-wear regimes in these maps suggests that it may be possible to optimise actual machining operations so that compromises between rates of material removal, for an acceptable level of productivity, and tool costs can be reached. The concept of using machining-regions maps for practical tool-wear minimisation during machining is also discussed.     

Surface generation modeling of micro milling process with stochastic tool wear

Micro milling is widely used to manufacture miniature parts and features at high quality with low set-up cost. To achieve a higher quality of existing micro products and improve the milling performance, a reliable analytical model of surface generation is the prerequisite as it offers the foundation for surface topography and surface roughness optimization. In the micro milling process, the stochastic tool wear is inevitable, but the deep influence of tool wear hasn't been considered in the micro milling process operation and modeling. Therefore, an improved analytical surface generation model with stochastic tool wear is presented for the micro milling process. A probabilistic approach based on the particle filter algorithm is used to predict the stochastic tool wear progression, linking online measurement data of cutting forces and tool vibrations with the state of tool wear. Meanwhile, the influence of tool run-out is also considered since the uncut chip thickness can be comparable to feed per tooth compared with that in conventional milling. Based on the process kinematics, tool run-out and stochastic tool wear, the cutting edge trajectory for micro milling can be determined by a theoretical and empirical coupled method. At last, the analytical surface generation model is employed to predict the surface topography and surface roughness, along with the concept of the minimum chip thickness and elastic recovery. The micro milling experiment results validate the effectiveness of the presented analytical surface generation model under different machining conditions. The model can be a significant supplement for predicting machined surface prior to the costly micro milling operations, and provide a basis for machining parameters optimization.     

Multi-scale statistical signal processing of cutting force in cutting tool condition monitoring

The International Journal of Advanced Manufacturing Technology - In a machining system, accurate tool wear condition monitoring is paramount for guaranteeing the quality of the workpiece and tool...     

Optimum design of cam-roller follower mechanism using a new evolutionary algorithm

Selection of tooling to perform specific operations like drilling and milling on ceramic materials using rotary ultrasonic machining process is an important aspect to meet stringent dimensions on workpiece as well as intended performance of tool. This phenomenon is more critical for micro rotary ultrasonic machining. In the present study, an effort was made to do micro drilling operation of Ø0.3 mm tool with varying geometry, having different wall thicknesses and abrasive grain sizes using design of experiments. The effect of tool-based parameters like grain size and wall thickness has been studied on axial cutting force, radial cutting force, tool wear, edge chipping area and taper. After examining axial and radial cutting forces, it has been concluded that lower wall thickness (80 μm) tool is good for drilling operation; and higher wall thickness (100 μm) tool is good for milling operation under same material removal rate conditions. It has been also investigated that lower wall thickness (80 μm) tool has less edge chipping area and less taper and can impart high drilling depth as compared to higher wall thickness (100 and 150 μm) tool. It is also concluded that lesser grain size (15 μm) tools are advantageous in terms of edge chipping area and cutting force for drilling and milling operations as compared to higher grain size (30, 35 and 45 μm) tool at constant material removal rate. Higher grain size tools have been broken at 1.13 mm³/h material removal rate conditions due to bad profile accuracy. But higher grain size tools have worked fairly well at less material removal rate condition. Higher grain size tools produced less wear. Tool wear was found minimum in higher wall thickness (100 μm) tool having higher abrasive grain size (30 μm). Using inferred results, Ø0.3 mm drilling experiments have been carried out on six aerospace ceramic materials. Also, groove of 0.5 mm size using Ø0.3 mm optimised tool has been successfully carried out in sintered SiC.     

Tribological compatibility and improvement of machining productivity and surface integrity

Machining process productivity and machined part quality improvement is a considerable challenge for modern manufacturing. One way to accomplish this is through the application of PVD coatings on cutting tools. In this study the wear rate and wear behavior of end milling cutters with mono-layered TiAlCrN and nano-multilayered self-adaptive TiAlCrN/WN PVD coatings have been studied under high performance dry ball-nose end-milling conditions. The material being machined in this case is hardened H13 tool steel. The morphology of the worn surface of the cutting tool has been studied using SEM/EDX. The microstructure of the cross-section of the chips formed during cutting was analyzed as well. The surface integrity of the workpiece material was also evaluated. Surface roughness and microhardness distribution near the surface of the workpiece material was also investigated. The data presented shows that achieving a high degree of tribological compatibility within the cutting tool/workpiece system can have a big impact on tool life and surface integrity improvement during end milling of hardened tool steel.     

基于主轴电流的铣削力间接监测方法

实时准确地监测铣削状态对于提高加工质量与加工效率具有重要意义,切削力作为重要的加工状态监测对象,因其监测设备昂贵且安装不便而受到限制,为此提出一种考虑刀具磨损的基于主轴电流的铣削力监测方法.首先基于切削微元理论建立了考虑后刀面磨损的铣削力模型,并通过铣削实验进行铣削力模型系数标定;然后对主轴电流与铣削力的关系进行理论建...