超声振动改善深孔镗削加工质量

深孔加工在航空发动机制造过程中广泛存在,由于其刚性弱,静态让刀量大,导致加工颤振和刀具磨损严重,使得其加工质量难以得到保证。超声振动切削作为一种特种切削加工手段,具有降低切削力,提高系统刚性和抑制加工颤振等优势。将超声振动应用于深孔镗削,进行了断屑条件验证,孔径误差测量,已加工表面粗糙度测量以及表面形貌观测等试验。试验结果表明,超声振动镗削能够有效缓解深孔镗削过程中的堵屑问题,减小孔径误差和表面粗糙度,抑制切削颤振,从而改善深孔镗削加工质量。     

MODELING OF 5-AXIS MILLING PROCESSES

5-axis milling operations are common in several industries such as aerospace, automotive and die/mold for machining of sculptured surfaces. In these operations, productivity, dimensional tolerance integrity and surface quality are of utmost importance. Part and tool deflections under high cutting forces may result in unacceptable part quality whereas using conservative cutting parameters results in decreased material removal rate. Process models can be used to determine the proper or optimal milling parameters for required quality with higher productivity. The majority of the existing milling models are for 3-axis operations, even the ones for ball-end mills. In this article, a complete geometry and force model are presented for 5-axis milling operations using ball-end mills. The effect of lead and tilt angles on the process geometry, cutter and workpiece engagement limits, scallop height, and milling forces are analyzed in detail. In addition, tool deflections and form errors are also formulated for 5-axis ball-end milling. The use of the model for selection of the process parameters such as lead and tilt angles that result in minimum cutting forces are also demonstrated. The model predictions for cutting forces and tool deflections are compared and verified by experimental results.     

MODELING OF 5-AXIS MILLING PROCESSES

5-axis milling operations are common in several industries such as aerospace, automotive and die/mold for machining of sculptured surfaces. In these operations, productivity, dimensional tolerance integrity and surface quality are of utmost importance. Part and tool deflections under high cutting forces may result in unacceptable part quality whereas using conservative cutting parameters results in decreased material removal rate. Process models can be used to determine the proper or optimal milling parameters for required quality with higher productivity. The majority of the existing milling models are for 3-axis operations, even the ones for ball-end mills. In this article, a complete geometry and force model are presented for 5-axis milling operations using ball-end mills. The effect of lead and tilt angles on the process geometry, cutter and workpiece engagement limits, scallop height, and milling forces are analyzed in detail. In addition, tool deflections and form errors are also formulated for 5-axis ball-end milling. The use of the model for selection of the process parameters such as lead and tilt angles that result in minimum cutting forces are also demonstrated. The model predictions for cutting forces and tool deflections are compared and verified by experimental results.     

Experimental and numerical investigation of cutting forces in micro-milling of polycarbonate glass

Abstract

Polycarbonates have found important applications in various types of industries including optical, automotive, aerospace, biomedical, and defense manufacturing industries. Conventional mechanical machining has the capability to create complex multi-scale parts and components for various materials including polymeric materials. This study investigates the cutting forces generated during the machining of polycarbonate glass using the micro-milling process. The goal of this research is to machine high quality micro-channels in polycarbonates for microfluidic applications. Both experimental investigation and numerical simulations using the Finite Element Method (FEM) have been carried out to assess the cutting forces generated in three directions during machining of polycarbonate. The effectiveness of tool coating on the reduction of cutting forces has been investigated. It was found that with the careful combination of depth of cut and feed rate, the ductile mode machining of polycarbonate can be achieved, which produces lower cutting forces, that could result in improved surface finish and low tool wear. Both lower and higher of depths of cut were found to generate higher cutting forces due to dragging action and higher tool-workpiece contact area respectively. The Finite Element Method (FEM) was found to be effective in simulating the cutting forces with acceptable range of errors, and thus, could be used to predict cutting forces at the parametric combinations beyond the capacity of the machine or without carrying out further expensive experimentation, for which the chances of tool failure are higher.     

CORRELATION-BASED ESTIMATION OF CUTTING FORCE COEFFICIENTS FOR BALL-END MILLING

This article presents a methodology to estimate cutting force coefficients based on the least squares approximation using correlation factor between the estimated and measured cutting forces in order to determine the corresponding tool angular position. This method can be applied on measured cutting force data over any small interval of time that need not contain information of the time instant when the cutting tool enters the workpiece, which has been the main requirement in the conventional method. This allows a quick estimation of the cutting force coefficients regardless of the chosen cutting conditions and tool-workpiece material, which is often the case in industrial machining processes. This proposed method has been validated by comparison of cutting force coefficients obtained using conventional estimation technique for a slot ball-end milling test. Besides being useful for predictive evaluation of forces, such estimation of cutting force coefficients of the cutting force model can be useful for understanding variations in cutting process over the tool life and can assist in online monitoring and process optimization.     

Prediction of cutting forces in helical milling process

The prediction of cutting forces is important for the planning and optimization of machining process in order to reduce machining damage. Helical milling is a kind of hole-machining technique with a milling tool feeding on a helical path into the workpiece, and thus, both the periphery cutting edges and the bottom cutting edges all participated in the machining process. In order to investigate the characteristics of discontinuous milling resulting in the time varying undeformed chip thickness and cutting forces direction, this paper establishes a novel analytic cutting force model of the helical milling based on the helical milling principle. Dynamic cutting forces are measured and analyzed under different cutting parameters for the titanium alloy (Ti–6Al–4V). Cutting force coefficients are identified and discussed based on the experimental test. Analytical model prediction is compared with experiment testing. It is noted that the analytical results are in good agreement with the experimental data; thus, the established cutting force model can be utilized as an effective tool to predict the change of cutting forces in helical milling process under different cutting conditions.     

A model-based approach for monitoring of shape deviations in peripheral milling

This paper presents a model-based approach for monitoring of shape deviations for milling operations. In order to detect occurring shape deviations of the machined workpiece during the milling process, different kinds of process models are presented and discussed for their application on manufacturing quality monitoring. Thereby, a model-based system was presented for the monitoring of shape deviations based on measured cutting forces. For the transformation of cutting forces into shape deviations, a tool deflection model and material removal model were designed and applied to a monitoring system. The presented model-based monitoring approach delivers accurate quality information, like geometric shape deviations, which can be monitored against geometric tolerances, providing a quality monitoring of manufacturing processes. The reconstruction of shape deviations from measured cutting forces is verified experimentally by comparing measured and reconstructed shape contours.     

Mathematical model of micro turning process

In recent years, significant advances in turning process have been achieved greatly due to the emergent technologies for precision machining. Turning operations are common in the automotive and aerospace industries where large metal workpieces are reduced to a fraction of their original weight when creating complex thin structures. The analysis of forces plays an important role in characterizing the cutting process, as the tool wear and surface texture, depending on the forces. In this paper, the objective is to show how our understanding of the micro turning process can be utilized to predict turning behavior such as the real feed rate and the real cutting depth, as well as the cutting and feed forces. The machine cutting processes are studied with a different model compared to that recently introduced for grinding process by Malkin and Guo (2006). The developed two-degrees-of-freedom model includes the effects of the process kinematics and tool edge serration. In this model, the input feed is changing because of current forces during the turning process, and the feed rate will be reduced by elastic deflection of the work tool in the opposite direction to the feed. Besides this, using the forces and material removal during turning, we calculate the effective cross-sectional area of cut to model material removal. With this model, it is possible for a machine operator, using the aforementioned turning process parameters, to obtain a cutting model at very small depths of cut. Finally, the simulated and experimental results prove that the developed mathematical model predicts the real position of the tool tip and the cutting and feed forces of the micro turning process accurately enough for design and implementation of a cutting strategy for a real task.     

多刃均布式镗杆系统振动耦合问题研究

深孔镗削过程中,由于镗杆的悬伸量较大,刚度差,强度低,在镗削过程中易产生振动。自激振动是金属切削过程中产生的振动类型之一,同时其振动机理的揭示以及对它的控制相对于受迫振动的研究而言较为困难。本文针对多刃均布式镗杆系统,在建立其力学模型的基础上,计算镗刀所受的动态切削力,并对镗杆振动系统耦合微分方程进行推导计算,对该耦合系统的稳定性进行分析,最后得出引起该系统产生自激振动的条件。     

Experimental investigations of surface roughness in orthogonal turning of unidirectional glass-fiber reinforced plastic composites

Cutting parameters and the resulting cutting forces have a great effect on the machinability of materials during the turning process. The effects of cutting parameters on machinability have been examined by many researchers and studies on determination of suitable cutting conditions for various materials are still under investigation. In this study, surface roughness of unidirectional glass-fiber reinforced plastic composite was examined on the basis of cutting parameters such as depth of cut, feed rate, tool geometry, and cutting speed. The surface quality was found to relate closely to the feed rate, cutting speed, and cutting tool.     

Tool paths and cutting technology in computer-aided process planning

This paper reports on the development of a module to calculate automatically tool paths and cutting conditions for metal cutting operations. Process planning must select correct cutting conditions to minimise disturbances on the shop floor owing to tooling problems. Tool path and cutting condition algorithms to generate reliable NC programs have been designed. The algorithms have been implemented in the framework of a generative computer-aided process planning system, called PART. Geometrical requirements to avoid chipping of cutting teeth are considered in tool-path calculation. The cutting conditions are calculated using metal cutting process models. A method has been developed to calculate cutting forces for milling operations based on experimental data of cutting forces in turning. In the process models, various constraints of the machine tool, cutting tool, and the workpiece are considered.     

Modeling cutter tilt and cutter-spindle stiffness for machine condition monitoring in face milling using high-definition surface metrology

In face milling, the spindle is intentionally tilted to avoid backcutting. The cutter tilt during machining is a combined effect of the intentional initial tilt and cutter-spindle deflection, which varies with cutting load during machining. An accurate estimation of the cutter tilt is critical to surface quality control and machine health monitoring. However, due to the small magnitude, the spindle tilt and deflection are difficult to measure in real time. Conventionally, the cutter tilt can be obtained through in-line sensors mounted on the machine tool but such in-line measurement is greatly influenced by the dynamic machining conditions such as vibration. This paper proposes a method to monitor the spindle setup tilt and deflection using surface data measured by high-definition metrology (HDM). Two parameters are proposed to characterize the cutter tilt, i.e., cutter tilt at idle state (initial cutter tilt) for spindle setup and cutter-spindle stiffness for the cutter-spindle deflection. Cutting force modeling is conducted to estimate these two parameters in conjunction with statistical procedures that fit the model to HDM surface data. The estimated cutter-spindle stiffness variation is also correlated to machine conditions such as a loose or worn bearing for process diagnosis. The method is demonstrated via experimental data from a machining process for automotive engine heads.     

Extraction of 5-axis milling conditions from CAM data for process simulation

5-axis milling is widely used in machining of parts with free-form surfaces and complex geometries. Although in general 5-axis milling increases the process capability, it also brings additional challenges due to complex process geometry and mechanics. In milling, cutting forces, tool deflections, and chatter vibrations may reduce part quality and productivity. By use of process simulations, the undesired results can be identified and overcome, and part quality and productivity can be increased. However, machining conditions and geometry, especially the tool–work engagement limits, are needed in process models which are used in these simulations. Due to the complexity of the process geometry and continuous variation of tool–work engagement, this information is not readily available for a complete 5-axis milling cycle. In this study, an analytical method is presented for the identification of these parameters from computer-aided manufacturing data. In this procedure, depths of cut, lead, and tilt angles, which determine the tool–workpiece engagement boundaries, are directly obtained the cutter location file analytically in a very fast manner. The proposed simulation approach is demonstrated on machining of parts with relatively complex geometries.     

On high-speed turning of a third-generation gamma titanium aluminide

Gamma titanium aluminides are heat-resistant intermetallic alloys predestined to be employed in components suffering from high mechanical stresses and thermal loads. These materials are regarded as difficult to cut, so this makes process adaptation essential in order to obtain high-quality and defect-free surfaces suitable for aerospace and automotive parts. In this paper, an innovative approach for longitudinal external high-speed turning of a third-generation Ti-45Al-8Nb-0.2C-0.2B gamma titanium aluminide is presented. The experimental campaign has been executed with different process parameters, tool geometries and lubrication conditions. The results are discussed in terms of surface roughness/integrity, chip morphology, cutting forces and tool wear. Experimental evidence showed that, due to the high cutting speed, the high temperatures reached in the shear zone improve chip formation, so a crack-free surface can be obtained. Furthermore, the use of a cryogenic lubrication system has been identified in order to reduce the huge tool wear, which represents the main drawback when machining gamma titanium aluminides under the chosen process conditions.     

An improved methodology for the experimental evaluation of tool runout in peripheral milling

The modeling of cutting forces plays an important role in the progress of research and technology in most machining processes. In particular, peripheral milling is a cutting process difficult to model due to the large number of variables involved. Among these variables, tool runout affects process performance by modifying milling force patterns, shortening the tool life and machine components, and by degrading workpiece quality. In this paper, a methodology to evaluate tool runout in peripheral milling is presented. The use of a boring toolholder is proposed to make controllable changes in the tool offset that modifies tool runout. In addition, the proposed methodology has been validated by means of a piezoactuator-based system that allows tool runout compensation through controlling workpiece displacement. Experimental and simulated results presented in this paper reveal the practical applications of this methodology for researchers and engineers involved in the practice of milling and its modeling.     

ANALYTICAL MODELING OF THE EFFECT OF THE TOOL FLANK WEAR WIDTH ON THE RESIDUAL STRESS DISTRIBUTION

Tool flank wear has significant effects on the cutting process, as it affects cutting forces, temperature and residual stresses. In this article, analytical models are developed to predict the cutting temperature and residual stresses in the orthogonal machining of a worn tool. In these models, measured forces, cutting conditions, tool geometry, and material properties are used as inputs. Stresses resulting from thermal stresses, fresh tool stresses and stresses due to tool flank wear are used in this analytical elasto-plastic model, and the residual stresses are determined by a relaxation procedure. The analytical model is verified experimentally with X-ray diffraction measurements. With the analytical model presented here, accurate residual stress profiles in worn tools are shown, while the computational time is significantly reduced from days, typical for finite-element method (FEM) models, to seconds.     

Feature signature prediction of a boring process using neural network modeling with confidence bounds

Prediction of machine tool failure has been very important in modern metal cutting operations in order to meet the growing demand for product quality and cost reduction. This paper presents the study of building a neural network model for predicting the behavior of a boring process during its full life cycle. This prediction is achieved by the fusion of the predictions of three principal components extracted as features from the joint time–frequency distributions of energy of the spindle loads observed during the boring process. Furthermore, prediction uncertainty is assessed using nonlinear regression in order to quantify the errors associated with the prediction. The results show that the implemented Elman recurrent neural network is a viable method for the prediction of the feature behavior of the boring process, and that the constructed confidence bounds provide information crucial for subsequent maintenance decision making based on the predicted cutting tool degradation.NSF Industry/University Cooperative Research Center (NSF I/UCRC) forIntelligent Maintenance Systems(IMS).     

螺旋铣孔工艺的切削稳定性及工艺参数规划

以螺旋铣孔工艺时域解析切削力建模、时域与频域切削过程动力学建模、切削颤振及切削稳定性建模为基础,研究了螺旋铣孔的切削参数工艺规划模型和方法。切削力模型同时考虑了刀具周向进给和轴向进给,沿刀具螺旋进给方向综合了侧刃和底刃的瞬时受力特性;动力学模型中同时包含了主轴自转和螺旋进给两种周期对系统动力学特性的影响,并分别建立了轴向切削稳定域和径向切削稳定域的预测模型,求解了相关工艺条件下的切削稳定域叶瓣图。在切削力和动力学模型基础之上,研究了包括轴向切削深度、径向切削深度、主轴转速、周向进给率、轴向进给率等切削工艺参数的多目标工艺参数规划方法。最后通过试验对所规划的工艺参数进行了验证,试验过程中未出现颤振现象,表面粗糙度、圆度、圆柱度可以达到镗孔工艺的加工精度。     

PREDICTION AND EXPERIMENTAL ANALYSIS OF CUTTING FORCES DURING MACHINING OF PRECISION EXTERNAL THREADS

External thread cutting is a complex 3-D process in which the cutting conditions vary over the thread cutter profile. It is accepted as a mature; however, heavily experience based technology and there are few academic work published. Determining the cutting forces during machining is crucial to explain formation of the surface layer, residual stresses, selection of the most appropriate machine tool and optimizing the process. This investigation is an attempt to predict thread cutting forces by dividing the thread chip into three parts, one thread root and two side faces. Variation of the cutting parameters including the shear angle, mean cutting temperature and friction force on the flank face of the tool along the thread tool root and sides are determined. In the thread root and sides, chip compression ratios for the V-shaped single piece and separately cut chip zones are measured and cutting forces are calculated and compared for precision metric thread cutting on a SAE 4340 steel bar.     

Cutting parameter and tool path style effects on cutting force and tool deflection in machining of convex and concave inclined surfaces

Convex and concave inclined surfaces are frequently encountered in the machining of components in industries such as aerospace, aircraft, automotive, biomedical, and precision machinery manufacturing and mold industries. Tool path styles, generated by different cutting strategies, result in various cutting forces and tool deflection values that might lead to poor surface integrities. In cost-effective manufacturing, it is helpful to make known their effects on machinability. Thus, the first aim of this study is to investigate optimum cutting parameter values in ball end milling of EN X40CrMoV5-1 tool steel with three coated cutters. The parameters taken into consideration are cutting speed, feed rate, step over, and tool path style. The second aim of the study is to determine the effects of tool path styles in ball end milling of inclined surfaces. As a result, the most effective parameter within the selected cutting parameters and cutting styles for both inclined surfaces and different coatings was step over. In terms of tool coatings, the most rapidly deteriorating coating was TiC coating for cutting forces in both inclined surfaces and for tool deflection in convex inclined surface. In addition, the response surface methodology is employed to predict surface roughness values, depending on the cutting forces obtained. The model generated gives highly accurate results.