Optimization of cutting conditions during continuous finished profile machining using non-traditional techniques

Optimum machining parameters are of great concern in manufacturing environments, where economy of machining operation plays a key role in competitiveness in the market. Many researchers have dealt with the optimization of machining parameters for turning operations with constant diameters only. All Computer Numerical Control (CNC) machines produce the finished components from the bar stock. Finished profiles consist of straight turning, facing, taper and circular machining.This research work concentrates on optimizing the machining parameters for turning cylindrical stocks into continuous finished profiles. The machining parameters in multi-pass turning are depth of cut, cutting speed and feed. The machining performance is measured by the production cost.In this paper the optimal machining parameters for continuous profile machining are determined with respect to the minimum production cost subject to a set of practical constraints. The constraints considered in this problem are cutting force, power constraint, tool tip temperature, etc. Due to high complexity of this machining optimization problem, six non-traditional algorithms, the genetic algorithm (GA), simulated annealing algorithm (SA), Tabu search algorithm (TS), memetic algorithm (MA), ants colony algorithm (ACO) and the particle swarm optimization (PSO) have been employed to resolve this problem. The results obtained from GA, SA,TS, ACO, MA and PSO are compared for various profiles. Also, a comprehensive user-friendly software package has been developed to input the profile interactively and to obtain the optimal parameters using all six algorithms. New evolutionary PSO is explained with an illustration .     

Optimisation of the electrical discharge machining process using a GA-based neural network

In this paper, the optimisation of the EDM process parameters from the rough cutting stage to the finish cutting stage has been reported. A trained neural network was used to establish the relationship between the process parameters and machining performance. Genetic algorithms with properly defined objective functions were then adapted to the neural network to determine the optimal process parameters. Examples with specifications intentionally assigned the same values as those recorded in the database or selected arbitrarily have been fed into the developed GA-based neural network in order to verify the optimisation ability throughout the machining process. Accordingly, the optimised results indicate that the GA-based neural network can be successfully used to generate optimal process parameters from the rough cutting stage to the finish cutting stage.     

司太立合金堆焊件的车削加工

分析了堆焊司太立合金的切削加工性能,分别针对司太立合金堆焊件的粗、精车削加工提出高效加工方法,讨论了刀具选择、切削用量的选择等重点问题并进行了切削效果的对比。     

中大型深沟球轴承外圈沟道精仿工艺

仿形车床C7232原来用于中型深沟球轴承外圈沟道的粗加工,精加工由成型车刀完成。由于产品转型,加工直径变为φ250mm～φ320mm之间,沟道变宽使切削力增加,精车工序无法由成型刀完成。针对以上问题,用C7232车床进行精车试验,圆满完成中大型产品外沟道精加工,质量符合要求。     

On the influence and optimisation of cutting parameters in finishing of metallic femoral heads of hip implants

Roughness and sphericity are two important factors affecting friction and lubrication performance of femoral heads of hip implants. Precision finishing of femoral heads is therefore crucial. This paper presents the effect and optimisation of key machining parameters in finish turning of metallic femoral heads, with an aim to achieve the best surface roughness and sphericity. Three important machining variables—cutting speed, feed rate and depth of cut—were considered. According to Taguchi methodology, a factorial design of experiments was planned to capture the effect of machining variables. A series of single-pass finish turning tests was conducted on a 28-mm femoral head made of biomedical grade stainless steel AISI 316 L by using tungsten carbide inserts. We used the analysis of variance (ANOVA) to elucidate the influence of the dominant parameters, which led to derive a regression model and response surface to estimate the desired machining responses. The results suggest that, among all cutting parameters, feed rate affects significantly surface roughness, while both feed rate and depth of cut are the dominant factors impacting markedly sphericity. Using desirability function-based criteria, single response and multiresponse optimisations were performed to determine an optimum combination of machining parameters. The objective was to maximise the desirability under the given range of parameters. Optimisation results show that cutting speed of 280.02 m/min, feed rate of 0.1 mm/rev and depth of cut of 0.2 mm are the optimum set, which is expected to provide minimum surface roughness and sphericity of the finished femoral heads. The parameters are thus expected to minimise further polishing time and improve manufacturing productivity.     

双刀并行数控车削中的切削参数优化方法

为优化双刀并行车削中的切削参数,降低加工成本,提出了结合蚁群算法和子问题枚举算法的切削参数优化算法。以最小化加工成本为目标函数,以粗精车削两阶段的切削参数为决策变量,建立了双刀并行车削的切削参数优化模型;根据车削加工的特点,将参数优化问题分解成若干个子问题,并推导出相应的加工成本理论下限,从而有效降低问题的复杂度。模拟结果表明,该算法运算效率高,能快速找到优化的车削参数,从而节约加工成本。     

Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing

The selection of optimal machining parameters plays an important part in computer-aided manufacturing. The optimisation of machining parameters is still the subject of many studies. Genetic algorithm (GA) and simulated annealing (SA) have been applied to many difficult combinatorial optimisation problems with certain strengths and weaknesses. In this paper, genetic simulated annealing (GSA), which is a hybrid of GA and SA, is used to determine optimal machining parameters for milling operations. For comparison, basic GA is also chosen as another optimisation method. An application example that has previously been solved using geometric programming (GP) method is presented. The results indicate that GSA is more efficient than GA and GP in the application of optimisation.     

Performance studies of multilayer hard surface coatings (TiN/TiCN/Al2O3/TiN) of indexable carbide inserts in hard machining: Part-I (An experimental approach)

In recent years, hard machining using CBN and ceramic inserts became an emerging technology than traditional grinding and widely used manufacturing processes. However the relatively high cost factors associated with such tools has left a space to look for relatively low cost cutting tool materials to perform in an acceptable range. Multilayer coated carbide insert is the proposed alternative in the present study due to its low cost. Thus, an attempt has been made to have an extensive study on the machinability aspects such as flank wear, chip morphology, surface roughness in finish hard turning of AISI 4340 steel (HRC 47 ± 1) using multilayer coated carbide (TiN/TiCN/Al₂O₃/TiN) insert under dry environment. Parametric influences on turning forces are also analyzed. From the machinability study, abrasion and chipping are found to be the dominant wear mechanism in hard turning. Multilayer TiN coated carbide inserts produced better surface quality and within recommendable range of 1.6 μm i.e. comparable with cylindrical grinding. At extreme parametric conditions, the growth of tool wear was observed to be rapid thus surface quality affected adversely. The chip morphology study reveals a more favorable machining environment in dry machining using TiN coated carbide inserts. The cutting speed and feed are found to have the significant effect on the tool wear and surface roughness from ANOVA study. It is evident that, thrust force (Fy) is the largest component followed by tangential force (Fz) and the feed force (Fx) in finish hard turning. The observations yield the machining ability of multilayer TiN coated carbide inserts in hard turning of AISI 4340 steel even at higher cutting speeds.     

The cutting tool stresses in finish turning of hardened steel with mixed ceramic tool

Precision hard machining is an interesting topic in manufacturing die and mold, automobile parts, and scientific research. While the hard machining has benefit advantages such as short cutting cycle time, process flexibility, and low surface roughness, there are several disadvantages such as high tooling cost, need of rigid machine tool, high cutting stresses, and residual stresses. Especially, tool stresses should be understood and dealt with to achieve successful performance of finish hard turning with ceramic cutting tool. So, the influence of cutting parameters on cutting stresses during dry finish turning of hardened (52 HRC) AISI H13 hot work steel with ceramic tool is investigated in this paper. For this aim, a series finish turning tests were performed, and the cutting forces were measured in tests. After literature procedure about finite element model (FEM), FEM is established to predict cutting stresses in finish turning of hardened AISI H13 steel with Ceramic 650 grade insert. As shown, effect of the cutting parameters on cutting tool stresses in finish turning of AISI H13 steel is obtained. The suggested results are helpful for optimizing the cutting parameters and decreasing the tool failure in finish turning applications of hardened steel.     

基于GSK980TD系统车削梯形螺纹的应用研究

梯形螺纹在数控车床上,尤其是在经济型数控车床上的加工存在扎刀现象,是比较难解决的问题。利用GSK980TD系统提供的宏功能解决了梯形螺纹编程困难的问题,为各种直径和螺距的梯形螺纹加工编制了通用的数控车削程序。在程序中巧妙地结合了普通车床车削梯形螺纹时应用的各种工艺技巧,采用分层切削、螺纹切削粗、精加工分段降低牙侧的表面粗糙度,为数控车削梯形螺纹提供了一个实用合理的加工程序。     

Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations

Optimization of cutting parameters is valuable in terms of providing high precision and efficient machining. Optimization of machining parameters for milling is an important step to minimize the machining time and cutting force, increase productivity and tool life and obtain better surface finish. In this work a mathematical model has been developed based on both the material behavior and the machine dynamics to determine cutting force for milling operations. The system used for optimization is based on powerful artificial intelligence called genetic algorithms (GA). The machining time is considered as the objective function and constraints are tool life, limits of feed rate, depth of cut, cutting speed, surface roughness, cutting force and amplitude of vibrations while maintaining a constant material removal rate. The result of the work shows how a complex optimization problem is handled by a genetic algorithm and converges very quickly. Experimental end milling tests have been performed on mild steel to measure surface roughness, cutting force using milling tool dynamometer and vibration using a FFT (fast Fourier transform) analyzer for the optimized cutting parameters in a Universal milling machine using an HSS cutter. From the estimated surface roughness value of 0.71 μm, the optimal cutting parameters that have given a maximum material removal rate of 6.0×10³ mm³/min with less amplitude of vibration at the work piece support 1.66 μm maximum displacement. The good agreement between the GA cutting forces and measured cutting forces clearly demonstrates the accuracy and effectiveness of the model presented and program developed. The obtained results indicate that the optimized parameters are capable of machining the work piece more efficiently with better surface finish.     

Fabricating micromilling tool using wire electrodischarge grinding and focused ion beam sputtering

In the present research, wire electrical discharge machining (WEDM) of γ titanium aluminide is studied. Selection of optimum machining parameter combinations for obtaining higher cutting efficiency and accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complicated stochastic process mechanisms. In general, no perfect combination exists that can simultaneously result in both the best cutting speed and the best surface finish quality. This paper presents an attempt to develop an appropriate machining strategy for a maximum process criteria yield. A feed-forward back-propagation neural network is developed to model the machining process. The three most important parameters – cutting speed, surface roughness and wire offset – have been considered as measures of the process performance. The model is capable of predicting the response parameters as a function of six different control parameters, i.e. pulse on time, pulse off time, peak current, wire tension, dielectric flow rate and servo reference voltage. Experimental results demonstrate that the machining model is suitable and the optimisation strategy satisfies practical requirements.     

Environmentally conscious hard turning of cemented carbide materials on the basis of micro-cutting in SEM (2nd report): stress turning with three kinds of cutting tools

Environmentally conscious hard turning and technology have placed increasing importance on the machining process. Cutting fluids have a significant impact on the environment, thus numerous research works are being performed to minimize their use. However, tool wear is very severe in hard turning cemented carbides without the use of cutting fluids. In this research, the effects of dry and wet cutting methods (vegetable oil mist and mineral oil) and tool material on cutting resistance and wear characteristics of cutting tools were experimentally investigated to study the possibility of creating an environmentally conscious hard turning of cemented carbides. Mist and wet cutting of the cemented carbides using poly-crystalline diamond (PCD) cutting tools were adopted to investigate how tool wear on the basis of micro-cutting in the Scanning Electron Microscope (SEM) can be reduced. Additionally, the poly-crystalline cubic boron nitride (PcBN) and the usual cBN cutting tools were compared with the PCD cutting tools. This paper was presented at the 9^th Asian International Conference on Fluid Machinery (AICFM9), Jeju, Korea, October 16–19, 2007.recommended for publication in revised form by Associate Editor Dae-Eun Kim HEO Sung Jung was born in Busan, R. O. K., in 1958. He received the Ph.D. in Mechanical Engineering from Osaka University, Osaka, Japan. He is a Full Professor of Mechanical Engineering at Doowon Technical College, Ansong -si, Gyonggi-do, Republic of Korea. His current research interests are in the areas of cutting of difficult-to-cut materials, environmentally conscious machining and cutting tool design.     

Optimization of cutting conditions of YG15 on rough and finish cutting in WEDM based on statistical analyses

In this paper, the effects and the optimization of cutting parameters on surface roughness (Ra) and material removal rate (MRR) in the wire electrical discharge machining (WEDM) of high hardness tool steel YG15 are analyzed. In the WEDM process, the key process parameters, such as pulse-on time, pulse-off time, power, cutting feed rate, wire tension, wire speed, and water pressure, are optimized. Experimental data were initially collected based on the Taguchi method of experimental design, which are $L_{18}\left (2^1\times 3^5\right )$ and $L_{18}\left (2^1\times 3^4\right )$ Taguchi standard orthogonal array on rough and finish cutting experiments, respectively. The level of importance of the cutting parameters on the Ra and MRR was determined on both finish and rough cutting by using statistical analyses; average gap voltage is discussed in order to balance cutting efficiency and stability on both finish and rough cutting. In addition, comparative analysis of finish and rough cutting is drawn to analyze the difference between rough cutting and finish cutting. Then, regression models and signal-to-noise ratio are used to obtain the optimum cutting parameter combination. Finally, the results present the optimized MRR and Ra of the rough and finish process, respectively, and confirm the efficiency and abilities of the model.     

Comparative Analysis of Conventional and Non-Conventional Optimisation Techniques for CNC Turning Process

This paper describes various optimisation procedures for solving the CNC turning problem to find the optimum operating parameters such as cutting speed and feedrate. Total production time is considered as the objective function, subject to constraints such as cutting force, power, tool–chip interface temperature and surface roughness of the product. Conventional optimisation techniques such as the Nelder Mead simplex method and the boundary search procedure, and non-conventional techniques such as genetic algorithms and simulated annealing are employed in this work. An example is given to illustrate the working procedures for determining the optimum operating parameters. Results are compared and their performances are analysed.     

471型管端车丝机外圆加工刀具的改进

为解决 471型管端车丝机加工石油套管时管端螺纹锥度不规则变化的问题 ,对外圆加工刀具几何参数作了合理改进 ,从而减小了外圆加工时钢管所受径向切削力 ,保证了管端螺纹锥度的精度稳定性     

Measurement of nose radius wear in turning tools from a single 2D image using machine vision

Flank and crater wear in cutting tools have been extensively studied in the past using direct and indirect methods. In finish and hard turning, however, nose radius wear plays a greater role in determining the surface quality of the finished product. This is due to the direct interaction between the tool nose area and the workpiece during machining. Nose radius wear can be measured from the 2D profiles of the tool before and after machining using a vision method. This approach, however, requires two images of cutting tools to be recorded and precisely aligned before subtraction. This work proposes a new method of measuring nose wear area from a single 2D image of the worn tool. The nose profile is extracted in the Cartesian coordinates and converted to a polar-radius plot. From the plot, the nose wear area is determined by simple subtraction.     

数控车宏程序的研究

在数控车床加工中有许多零件轮廓是椭圆、抛物线等二元二次曲线,而在数控车床编程里没有直接对应的指令可以加工二元二次曲线轮廓,需要用拟合曲线或者宏程序进行编程。就FANUC-0i系统数控车床手动编制宏程序,运用G73粗车封闭切削循环指令与G70精加工循环指令配合,实现二元二次曲线的粗、精加工,方便灵活地编写二次曲线曲线轮廓的宏程序。     

超声振动车削光整技术的试验研究

利用超声振动进行车削光整加工试验,对影响光整表面粗糙度的因素进行了大量的试验研究,通过对比试验和正交试验确定了合理的切削参数.分析了影响加工表面质量的一些因素,为推广使用超声振动车削光整工艺做出了试验上的分析和论证,分析了超声车削光整工艺的优越性和规律性。     

190柴油机曲轴数控铣削加工的分析探讨

曲轴是发动机的主要零件,其加工质量和加工效率直接影响发动机的工作性能和制造。曲轴粗加工采用CNC外铣加工工艺,使工件的加工精度、适应多品种生产的柔性和质量的稳定性都有了明显的改善。我厂引进了两台数控曲轴外铣铣床,特别适合于那些对平衡块侧面需要加工、轴颈没有沈割槽的曲轴。其较之车削、内铣等工艺,具有更高的生产效率。以济柴190型柴油机曲轴加工为实例,简要讲述了用数控曲轴铣床进行曲轴粗加工、半精加工的铣切工艺过程步骤和优点。