Process planning for reliable high-speed machining of moulds

A method of generating NC programs for the high-speed milling of moulds is investigated. Forging dies and injection moulds, whether plastic or aluminium, have a complex surface geometry. In addition they are made of steels of hardness as much as 30 or even 50 HRC. Since 1995, high-speed machining has been much adopted by the die-making industry, which with this technology can reduce its use of Sinking Electrodischarge Machining (SEDM). EDM, in general, calls for longer machining times. The use of high-speed machining makes it necessary to redefine the preliminary stages of the process. In addition, it affects the methodology employed in the generation of NC programs, which requires the use of high-level CAM software. The aim is to generate error-free programs that make use of optimum cutting strategies in the interest of productivity and surface quality. The final result is a more reliable manufacturing process. There are two risks in the use of high-speed milling on hardened steels. One of these is tool breakage, which may be very costly and may furthermore entail marks on the workpiece. The other is collisions between the tool and the workpiece or fixtures, the result of which may be damage to the ceramic bearings in the spindles. In order to minimize these risks it is necessary that new control and optimization steps be included in the CAM methodology. There are three things that the firm adopting high-speed methods should do. It should redefine its process engineering, it should systematize access by its CAM programmers to high-speed knowhow, and it should take up the use of process simulation tools. In the latter case, it will be very advantageous to use tools for the estimation of cutting forces. The new work methods proposed in this article have made it possible to introduce high speed milling (HSM) into the die industry. Examples are given of how the technique has been applied with CAM programming re-engineered as here proposed, with an explanation of the novel features and the results.     

Flank milling model for tool path programming of turbine blisks and compressors

In this paper, a methodology for complex surface machining based on cutting forces prediction is presented. The work is focused on blade finishing operations. The cutting forces model developed can be applied to three axis and five axis milling cases. For three-axis cases, the chip thickness is calculated according to traditional analytical methods. On the contrary, for five-axis cases the chip thickness is obtained from a geometric method developed in the paper. The cutting forces values can be calculated for the complete toolpath, but the presented model can also provide the programmer information about the cutting forces in a single point of the toolpath. The cutting force model is integrated in the CAM software in order to provide an extra tool that helps the programmer to decide which the optimal milling strategy is, based on the minimum cutting forces. In the last section, results of a case study based on impeller and blisk blades flank milling are discussed. Model predicted forces and real measured forces of flank milling operations are compared for model validation. Applying this methodology, cutting forces can be taken into account as a decisive criterion for optimal tool path selection.     

Studies on Machining Parameters While Milling Particle Reinforced Hybrid (Al6061/Al2O3/Gr) MMC

In this article, response surface methodology has been used for finding the optimal machining parameters values for cutting force, surface roughness, and tool wear while milling aluminum hybrid composites. In order to perform the experiment, various machining parameters such as feed, cutting speed, depth of cut, and weight (wt) fraction of alumina (Al₂O₃) were planned based on face-centered, central composite design. Stir casting method is used to fabricate the composites with various wt fractions (5%, 10%, and 15%) of Al₂O₃. The multiple regression analysis is used to develop mathematical models, and the models are tested using analysis of variance (ANOVA). Evaluation on the effects and interactions of the machining parameters on the cutting force, surface roughness, and tool wear was carried out using ANOVA. The developed models were used for multiple-response optimization by desirability function approach to determine the optimum machining parameters. The optimum machining parameters obtained from the experimental results showed that lower cutting force, surface roughness, and tool wear can be obtained by employing the combination of higher cutting speed, low feed, lower depth of cut, and higher wt fraction of alumina when face milling hybrid composites using polycrystalline diamond insert.     

Design,evaluation and optimisation of cutter path strategies when high speed machining hardened mould and die materials

The use of high speed milling (HSM) for the production of moulds and dies is becoming more widespread. Critical aspects of the technology include cutting tools, machinability data, cutter path generation and technology. Much published information exists on cutting tools and related data (cutting speeds, feed rates, depths of cut, etc.). However, relatively little information has been published on the optimisation of cutter paths for this application. Most of the research work is mainly focused on cutter path generation with the main aim on reducing production time. Work with regards to cutter path evaluation and optimisation on tool wear, tool life, surface integrity and relevant workpiece machinability characteristics are scant. Therefore, a detailed knowledge on the evaluation of cutter path when high speed rough and finish milling is essential in order to improve productivity and surface quality. The paper details techniques used to reduce machining times and improve workpiece surface roughness/accuracy when HSM hardened mould and die materials. Optimisation routines are considered for the roughing and finishing of cavities. The effects of machining parameters notably feed rate adaptation techniques and cutting tools are presented.     

Tool life and surface integrity when milling inconel 718 with coated cemented carbide tools

Abstract

This paper presents a study of tool life and surface integrity while machining superalloy Inconel 718 using coated cemented carbide tools. In the machining of heat resistant superalloys used in aeronautical applications and classified as difficult‐to‐machine, tool life is an important parameter in evaluating the performance of the cutting tools. Surface quality of the workpiece is one of the important criteria in determining tool life. Our tests have been done under various combinations of speed, feed rate, and depth of cut to verify the change in surface roughness due to increasing tool wear. The behavior of the uncoated, TiN, and TiCN layers using various cutting conditions was analyzed. At the end, a choice of coating and optimization of the cutting conditions has been proposed.     

Dynamic phenomena in finish turning of hardened steels with cBN-based tools

The paper presents some findings of the investigation of finish turning of KhVG hardened steel (60–62 HRC) using a cutting tool with an insert made of a cubic boron nitride based composite (cBN-Si₃N₄ system). The influence of machining process variables on the cutting force components, vibrations, and machined surface roughness is clarified. The authors propose some practical recommendations of how to choose machining modes and conditions.     

New method of tool orientation determination by enveloping element for five-axis machining of spatial cam

A new methodology is presented for the determination of a feasible tool orientation of a ball-end milling cutter for collision and gouging avoidance in five-axis machining of spatial cam. Since the meshing element is used as a generating element for a spatial cam, the meshing element is in tangency with the spatial cam. The notion of the proposed collision-free method is that the ball-end milling cutter is confined within the meshing element. Based on envelope theory, homogeneous coordinate transformation and differential geometry, curvatures of the cam surface and the cutting tool are evaluated for interference checking. To evaluate machining efficiency, the contact length is calculated for various tool orientations. The toolpath is verified through a solid cutting simulation. The proposed methodology can be used to automate the programming of tool paths for five-axis machining of spatial cam.     

Nose radius and cutting speed effects during milling of AISI 304 material

Not only milling parameters, but also cutting tool properties affect the machining performance. Therefore, in the current work, the effect of nose radius and cutting speed on the wear, force, surface roughness and chip morphology in down and up milling of AISI 304 stainless steel was investigated. Machining experiments were conducted with cutting tools with radii of 0.4, 0.8 and 1.2?mm at various cutting speeds in both down and up milling. Experimental results showed that the main tool failure mechanisms and modes were adhesion, abrasion, chipping and fracture during milling with various nose radii. Cutting forces dropped with the increment in nose radius regardless of the cutting speed and milling direction, except for up milling at 100?m/min. From the experimental results, it was found that roughness diminished with increase in both nose radius and speed. Surface roughness and the resultant forces during up milling were found to be lower than that during down milling. It was observed that the increment in nose radius increased the edge serration in chip morphology.     

Experimental investigations on cryogenic cooling by liquid nitrogen in the end milling of hardened steel

Milling of hardened steel generates excessive heat during the chip formation process, which increases the temperature of cutting tool and accelerates tool wear. Application of conventional cutting fluid in milling process may not effectively control the heat generation also it has inherent health and environmental problems. To minimize health hazard and environmental problems caused by using conventional cutting fluid, a cryogenic cooling set up is developed to cool tool–chip interface using liquid nitrogen (LN₂). This paper presents results on the effect of LN₂ as a coolant on machinability of hardened AISI H13 tool steel for varying cutting speed in the range of 75–125 m/min during end milling with PVD TiAlN coated carbide inserts at a constant feed rate. The results show that machining with LN₂ lowers cutting temperature, tool flank wear, surface roughness and cutting forces as compared with dry and wet machining. With LN₂ cooling, it has been found that the cutting temperature was reduced by 57–60% and 37–42%; the tool flank wear was reduced by 29–34% and 10–12%; the surface roughness was decreased by 33–40% and 25–29% compared to dry and wet machining. The cutting forces also decreased moderately compared to dry and wet machining. This can be attributed to the fact that LN₂ machining provides better cooling and lubrication through substantial reduction in the cutting zone temperature.     

Investigations on hard machining of Impax Hi Hard tool steel

In this paper, experimental investigations are carried out by end milling process on hardened tool steel, Impax Hi Hard (Hardness 55 HRC) a newly developed tool steel material used by tool and die making industries. Experiments are performed with an aim to study performance investigations of machining parameters such as cutting speed, feed, depth of cut and width of cut with consideration of multiple responses viz. volume of material removed, tool wear, tool life and surface finish to evaluate the performance of PVD coated carbide inserts and ball end mill cutters. It has been observed through scanning electron microscope, X-ray diffraction technique (EDX) that chipping and adhesion are active tool wear mechanisms and saw-toothed chips are formed while machining of Impax Hi Hard steel. It is also noticed out that tool life is not enhanced while machining with minimum quantity lubricant than dry machining. From the investigations, it is observed that hard machining can be considered as an alternative to grinding and EDM, traditional methods of machining difficult-to-machine materials i.e. hardened steel with hardness greater than 50 HRC with a scope of improved productivity, increased flexibility, decreased capital expenses and reduced environmental waste.     

Ti6Al4V Titanium Alloy End Milling with Minimum Quantity of Fluid Technique Use

To reduce the use of cutting fluids in machining operations is a goal that has been searched in the industry due to environmental and human health problems that the cutting fluids cause. However, cutting fluids still promote the longer life of the cutting tool for many machining operations. This is the case of Ti6Al4V titanium milling operation using coated cemented carbide inserts. Therefore, the aim of this work is to study the feasible cutting conditions for use of minimal quantity of fluid (MQF) technique, i.e., conditions that make the tool life in MQF technique closer or higher than those obtained with the cutting without lubrication/cooling and cutting fluid jet without giving up productivity and the average roughness of the parts in the process. To achieve these objectives, several trials at Ti6Al4V end milling were performed by varying the cutting speed and feed rate with MQF application technique using vegetable cutting fluid compared with no lubrication/cooling and cutting with jet fluid to 8% aqueous emulsion. The main conclusion from this study was that the application of the MQF technique in Ti6Al4V end milling process increases the tool life and productivity and reduces the average surface roughness, while maintaining the same cutting conditions originally proposed in machining. Finally, microstructural analysis by scanning electron microscope (SEM) and energy dispersive spectrometry (EDS) was performed from cutting tools, and the main wear mechanisms when varying the lubrication/cooling systems employed were observed.     

Experimental Study of Surface Roughness and Tool Flank Wear during Hybrid Milling

Two advanced machining methods such as thermally enhanced machining and ultrasonic-assisted machining are recently considered in many studies. In this article, a new hybrid milling process is presented by gathering the characteristics of these two methods. In order to determine the axial depth of cut and engagement in the process, three-dimensional thermal finite-element analysis is applied to determine the dimensions of softened materials. Finite-element modal analysis is used to determine the dimensions and clamping state of the workpiece while cutting area has the highest vibration amplitude. Full factorial experimental design is applied to investigate the effect of hybrid machining parameters on the surface roughness and tool wear. Tool flank wear was investigated under the condition of constant cutting speed during different period of times. Hybrid milling process with an amplitude of 6 µm and a temperature of 900°C creates a surface with 42% lower roughness in comparison to conventional milling in feed 0.08 mm/tooth. In a study of tool flank wear, the results show that application of TEUAM decreases flank wear at least 16% in comparison to all other processes.     

Modeling and multi-response optimization of machining performance while turning hardened steel with self-propelled rotary tool

There are many advanced tooling approaches in metal cutting to enhance the cutting tool performance for machining hard-to-cut materials.The self propelled rotary tool(SPRT) is one of the novel approaches to improve the cutting tool performance by providing cutting edge in the form of a disk,which rotates about its principal axis and provides a rest period for the cutting edge to cool and allow engaging a fresh cutting edge with the work piece.This paper aimed to present the cutting performance of SPRT while turning hardened EN24 steel and optimize the machining conditions.Surface roughness(R_a) and metal removal rate(r_(MMR)) are considered as machining performance parameters to evaluate,while the horizontal inclination angle of the SPRT,depth of cut,feed rate and spindle speed are considered as process variables.Initially,design of experiments(DOEs) is employed to minimize the number of experiments.For each set of chosen process variables,the machining experiments are conducted on computer numerical control(CNC) lathe to measure the machining responses.Then,the response surface methodology(RSM) is used to establish quantitative relationships for the output responses in terms of the input variables.Analysis of variance(ANOVA) is used to check the adequacy of the model.The influence of input variables on the output responses is also determined.Consequently,these models are formulated as a multi-response optimization problem to minimize the R_a and maximize the r_(MMR)simultaneously.Non-dominated sorting genetic algorithmII(NSGA-II) is used to derive the set of Pareto-optimal solutions.The optimal results obtained through the proposed methodology are also compared with the results of validation experimental runs and good correlation is found between them.     

Multi-attribute optimization of end milling epoxy granite composites using TOPSIS

Epoxy granite composites are identified and recognized as better materials for machine tool applications due to inherent damping properties. However, end milling of these composites has not been explored much. Milling of epoxy granite composites presents a number of problems, namely, cutting forces and surface roughness appear during machining. This research work focuses on end milling of epoxy granite composite specimens using high-speed steel end mill cutter by varying the cutting conditions such as spindle speed and feed with a uniform depth of cut and selection of optimal machining parameters. The experimental runs of 27 different trials were carried out and three different attributes such as thrust force, tangential force, and surface roughness were analyzed. This research work presents a sequential procedure for machining parameters selection. Selection of optimal machining parameters is done on the basis of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method.     

Prediction and control of surface roughness for the milling of Al/SiC metal matrix composites based on neural networks

In recent years, there has been a significant increase in the utilization of Al/SiC particulate composite materials in engineering fields, and the demand for accurate machining of such composite materials has grown accordingly. In this paper, a feed-forward multi-layered artificial neural network (ANN) roughness prediction model, using the Levenberg-Marquardt backpropagation training algorithm, is proposed to investigate the mathematical relationship between cutting parameters and average surface roughness during milling Al/SiC particulate composite materials. Milling experiments were conducted on a computer numerical control (CNC) milling machine with polycrystalline diamond (PCD) tools to acquire data for training the ANN roughness prediction model. Four cutting parameters were considered in these experiments: cutting speed, depth of cut, feed rate, and volume fraction of SiC. These parameters were also used as inputs for the ANN roughness prediction model. The output of the model was the average surface roughness of the machined workpiece. A successfully trained ANN roughness prediction model could predict the corresponding average surface roughness based on given cutting parameters, with a 2.08% mean relative error. Moreover, a roughness control model that could accurately determine the corresponding cutting parameters for a specific desired roughness with a 2.91% mean relative error was developed based on the ANN roughness prediction model. Finally, a more reliable and readable analysis of the influence of each parameter on roughness or the interaction between different parameters was conducted with the help of the ANN prediction model.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00326-x     

Virtual simulation of five-axis machine tool with consideration of CNC interpolation,servo dynamics,friction, and geometric errors

Abstract

A virtual machine tool (VMT) simulation system which considers tool center point (TCP) interpolation, geometric errors, servo dynamics, and friction effects for a five-axis machine tool is developed in this paper. A novel five-axis interpolation method is proposed to ensure that maximum velocity constraints for each axis can be satisfied. The geometric error model, including lead screw, straightness, angular and squareness errors is built to analyze the volumetric errors within the working space. The model which includes rigid body motion, friction model and servo control loops is utilized to evaluate servo dynamics and non-linear effects. The errors caused by the locations, servo dynamics, and friction effects are integrated into the VMT simulation program. Simulation results of TCP trajectory are represented by small line segments to generate NC codes. Then the NC codes are fed into VERICUT software to perform virtual cutting. To evaluate the interpolation design, cutting experiments are carried out on the five-axis engraving machine with a PC-based controller. The performances using the proposed interpolation method are comparable with the commercial CNC controller from Heidenhain. The effects of different error sources on the surface are demonstrated by cutting the sculpture of a human face. Path overcut caused by servo dynamics is found at sharp corners, and volumetric errors cause obvious tool marks and poor surface roughness. The proposed methodology can serve as a useful tool in evaluating the behaviors of error sources during the design stage.     

Optimal selection of cutting parameters in multi-tool milling operations using a genetic algorithm

In the milling of large monolithic structural components for aircraft, 70–80% of the total cut volume is removed using high-speed roughing operations. In order to achieve the economic objective (i.e. optimal part quality in minimal machining time) of this process, it is necessary to determine the optimal cutting conditions while respecting the multiple constraints (functional and technological) imposed by the machine, the tool and the part geometry. This work presents a physical model called GA-MPO (genetic algorithm based milling parameter optimisation system) for the prediction of the optimal cutting parameters (namely, axial depth of cut (a _p), radial immersion (a _e), feed rate (f _t) and spindle speed (n)) in the multi-tool milling of prismatic parts. By submitting a preliminary milling process plan (i.e. CL data file) generated by CAM (computer-aided manufacturing) software, the developed system provides an optimal combination of process parameters (for each machining feature), respecting the machine–tool–part functional/technological constraints. The obtained prediction accuracy and enhanced functional capabilities of the developed system demonstrate its improved performance over other models available in the literature.     

Prediction of cutting force based on machining parameters on AL7075-T6 aluminum alloy by response surface methodology in end milling

Cutting forces modeling is the basic to understand the cutting process, which should be kept in minimum to reduce tool deflection, vibration, tool wear and optimize the process parameters in order to obtain a high quality product within minimum machining time. In this paper a statistical model has been developed to predict cutting force in terms of geometrical parameters such as rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed and axial depth of cut. Response surface methodology experimental design was employed for conducting experiments. The work piece material is Aluminum (Al 7075-T6) and the tool used is high speed steel end mill cutter with different tool geometry. The cutting forces are measured using three axis milling tool dynamometer. The second order mathematical model in terms of machining parameters is developed for predicting cutting forces. The adequacy of the model is checked by employing ANOVA. The direct effect of the process parameter with cutting forces are analyzed, which helps to select process parameter in order to keep cutting forces minimum, which ensures the stability of end milling process. The study observed that feed rate has the highest statistical and physical influence on cutting force.     

Adaptive nonlinear tool path optimization for five-axis machining

Current tool path computation in the CAM algorithms approximates the surface by piecewise linear interpolation. In the case of three-axis machining on a CNC machine the tool will exactly reproduce this computed tool path. However in the case of five-axis simultaneous machining the real tool path on the CNC machine will not follow the linear approximation computed by the conventional CAM algorithm. A new CAM algorithm is proposed which approximates the surface to be machined by a piecewise curved approximation. This curve represents the real tool path followed on the five-axis machine. This piecewise curved approximation is further optimized by formulating the tool path computation as the generation of a grid based on a variational smoothness penalty function. This new algorithm considerably improves the accuracy and reduces the number of blocks and machining time.