数控加工参数优化技术研究

为了提高机床的利用率,需要在加工前通过对实际数控加工过程的仿真模拟来获取实际加工的最优化参数。在实际生产过程中,数控机床的加工工序不同,其所需要优化的目标就会有所不同,本文主要针对数控机床加工参数优化问题展开相应的探讨,通过建立数控加工的多目标优化模型进行仿真模拟,并结合遗传算法对每一种加工段进行加工参数优化,通过每一个特征段的优化累加可以获得实际的优化效果。经过实例证实,多元目标函数优化模型的优化效果良好。     

高效数控加工切削参数优化技术

数控加工切削参数的合理选择对高效数控切削加工技术的实现至关重要,数控切削加工工艺参数的优化有利于数控加工技术水平及效率的提高。本文针对300M钢在的正交实验结果进行切削参数分析,建立飞机起落架的切削参数优化模型,具有较高的推广价值。     

浅谈数控加工参数优化的研究现状与进展

现阶段数控加工技术在制造领域具有着十分显著的应用效果,逐渐得到了广泛应用,极大提升了机械制造行业的生产水平和效率.但在对数控加工技术进行实际应用过程中,如果没有合理设置和优化数控加工的参数,就会直接对机械制造效果、质量等造成影响.因此我们需要分析和论证数控加工参数,对数控加工参数优化的局限、现状等予以掌握,从而对数控加...     

数控加工切削参数优化研究

提出一种基于基因算法的切削参数优化方法——变搜索域遗传算法。与通常的优化算法相比，该方法计算量小，计算速度快，能适应自动化制造系统对优化切削数据快速响应的要求。在切削参数优化研究的基础上，针对成都飞机制造公司数控加工中心的实际情况，开发了数控加工切削参数管理和优化系统。该系统的完成和使用把工艺人员从大量的手工重复劳动中解放出来，并实现切削参数选取的科学化、合理化、规范化，为企业创造了良好的经济效益。     

基于VERICUT数控加工切削参数的优化

加工切削参数优化是指以最高生产率为目标函数,以最大主功率等为约束条件,按照用户设定的优化参数自动调整不同加工段的切削参数来保持恒定最大主功率状态,从而使单位时间内的材料切除量最大。使用仿真、验证与优化软件VERICUT,可以自动编制带有最佳参数的加工程序,减少或避免人工调整切削参数产生的种种问题,大幅度提高了加工效率和加工质量,为降低加工成本提供了有效的途径。     

数控车铣切削加工工艺参数优化分析

数控车铣在机械加工领域应用广泛,优化数控车铣切削加工的工艺参数,对提高工件质量与企业生产效益至关重要.基于此,介绍了数控车铣的基本组成与工作原理,阐述了编程数据处理、刀具的性能与参数、切削路线等影响数控车铣切削加工精度的因素,并结合数控车铣加工特点,对切削加工工艺参数进行了优化,以提高数控车铣加工精度,降低成本,提高效...     

基于QPSO的数控加工切削参数优化

QPSO是基于PSO的改进算法,具有全局搜索能力强,收敛速度快、鲁棒性高等特点。现利用QPSO对根据数控加工中机床和刀具的实际约束而建立的以进给量和切削速度为变量的数学模型进行优化,仿真结果表明经过QPSO优化得到的进给量和切削速度的值比经验值更能满足生产率最大化和生产成本最小化的要求,同时也明显优于PSO。     

数控切削加工工艺参数的多目标优化

基于数控车削和数控铣削加工工艺参数优化的数学描述 ,采用主要目标法和线性加权和法建立了多目标优化的数学模型 ,给出了以简便可靠的直接寻优算法实现多目标优化的计算实例     

不锈钢喷嘴数控加工工艺分析

通过对不锈钢喷嘴零件进行数控加工工艺分析,确定了合理的工艺路线和加工设备,实现了批量化生产.     

基于配置、优化参数解决数控加工精度超差的研究与实践

过切和欠切在数控加工中是一个比较常见的故障,严重影响加工品质。主要从优化参数方面着手,分析和处理在数控加工过程中出现的过切和欠切现象。     

Electrical discharge precision machining parameters optimization investigation on S-03 special stainless steel

S-03 is a novel special stainless steel, which is widely used in precision aerospace parts and electrical discharge machining technology has the merit of high-accuracy machining. This paper aims to combine gray relational analysis and orthogonal experimental to optimize electrical discharge high-accuracy machining parameters. The four process parameters of gap voltage, peak discharge current, pulse width, and pulse interval are required to optimize in the fewest experiment times. The material removal rate and surface roughness are the objective parameters. The experiment were carried out based on Taguchi L9 orthogonal array, then we carried out the gray relational analysis to optimize the multi-objective machining parameter, finally, we verified the results through a confirmation experiment. The sequence of machining parameters from primary to secondary are as follows: discharge current 7A, pulse interval 100 μs, pulse width 50 μs, and gap voltage 70 V. Using the above machining parameters, we can obtain good surface roughness Ra1.7 μm, and material removal rate 13.3 mm³/min. The machined work piece almost has no surface modification layer. The results show that combining orthogonal experiment and gray relational analysis can further optimize machining parameters, the material removal rate increased by 23.8 %, and the surface roughness almost has no change.     

An optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool for best surface finish

High-speed machining (HSM) has emerged as a key technology in rapid tooling and manufacturing applications. Compared with traditional machining, the cutting speed, feed rate has been great progress, and the cutting mechanism is not the same. HSM with coated carbide cutting tools used in high-speed, high temperature situations and cutting more efficient and provided a lower surface roughness. However, the demand for high quality focuses extensive attention to the analysis and prediction of surface roughness and cutting force as the level of surface roughness and the cutting force partially determine the quality of the cutting process. This paper presents an optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool to achieve minimum cutting forces and better surface roughness. Taguchi optimization method is the most effective method to optimize the machining parameters, in which a response variable can be identified. The standard orthogonal array of L₉ (3⁴) was employed in this research work and the results were analyzed for the optimization process using signal to noise (S/N) ratio response analysis and Pareto analysis of variance (ANOVA) to identify the most significant parameters affecting the cutting forces and surface roughness. For such application, several machining parameters are considered to be significantly affecting cutting forces and surface roughness. These parameters include the lubrication modes, feed rate, cutting speed, and depth of cut. Finally, conformation tests were carried out to investigate the improvement of the optimization. The result showed a reduction of 25.5% in the cutting forces and 41.3% improvement on the surface roughness performance.     

基于灰色关联分析的电火花加工不锈钢小孔工艺参数优化

采用DS307A高速穿孔机,开展在6mm厚不锈钢板上加工直径为1.2 mm小孔的试验研究。运用正交试验法,研究电火花加工电参数对加工时间、电极损耗和加工间隙的影响,并对试验结果进行灰色关联分析,得出最优加工参数。结果表明,经参数优化后,减少了加工时间、降低了电极损耗,以及表面粗糙度得以明显改善,满足快速精加工的技术要求。     

基于MATLAB的数控加工最短走刀路线研究

数控加工中工艺分析的一个重要环节就是寻找加工轨迹的最短路线,这样能充分发挥数控设备高效率的优点.当不能直观判断出最短走刀路线时,可通过建立合理的数学模型,运用MTLABL技术加以精确分析.介绍了建立数学模型和应用MTLABL的具体方法,结果表明此方法可行、便利,并为其他类型零件的走刀路线分析提供了借鉴实例.     

Study of machining parameters optimization for different materials in WEDM

In process planning of wire electrical discharge machining (WEDM), determination of appropriate machining conditions is likely to face problems in many ways. In addition to the construction of the relationship between machining parameters and machining characteristics, optimization search technique, a large number of experiments must be conducted repeatedly to renew parameters for different workpiece materials. The concept of specific discharge energy (SDE) was employed in this paper to represent the WEDM property of workpiece materials as one of the machining parameters. Two kinds of materials with distinctive SDE values, i.e., higher and lower, respectively, were selected for our experiments. The experimental data obtained were used, and a neural network that can accurately predict the relationship between machining parameters and machining characteristics was constructed. It was found that the predicted error was less than 7 %. The optimization technique of genetic algorithms was employed, and the optimal combination of machining parameters that meet the required machining characteristics for different workpiece materials was obtained. The system proposed in this study is both user-friendly and practical. It can save considerable time and cost during the construction of the database for the expert system of process planning.     

基于MATLAB轴承无心磨削工艺参数的优化

轴承零件对磨削技术和加工工艺要求很高,且生产效率低、成本高。为了得到满足条件的轴承零件,建立轴承零件无心磨削的数学模型,并应用MATLAB软件中的fmincon函数和遗传算法分别对工艺参数(工件线速度、磨轮线速度、径向进给量)进行求解优化,通过两种算法的结果对比选择一组更优的工艺参数进行生产验证,结果证明该组参数能使生产率大幅增加、生产成本显著下降。     

陶瓷刀具切削奥氏体不锈钢的切削力试验研究

对3种复合陶瓷材料刀具切削奥氏体不锈钢(1Cr17Ni7)进行研究,建立了正交切削试验方案.通过试验研究了切削用量对三向切削力的影响,利用指数回归分析建立了3种刀具的主切削力经验公式,并结合切削用量显著性分析对主切削力进行了对比分析.试验结果表明在采用较小进给量和较小切削深度进行切削时,会出现了背吃刀力大于主切削力的现象;切削速度及进给量对主切削力的影响最大;3种刀具中CT2刀具的主切削力最大.     

Study on optimized principles of process parameters for environmentally friendly machining austenitic stainless steel with high efficiency and little energy consumption

The International Journal of Advanced Manufacturing Technology - Green manufacturing is one of the important development directions for advanced manufacturing technology. In this paper, the...     

Genetic algorithm based optimization of the process parameters for gas metal arc welding of AISI 904 L stainless steel

The present study is focused on welding of super austenitic stainless steel sheet using gas metal arc welding process with AISI 904 L super austenitic stainless steel with solid wire of 1.2 mm diameter. Based on the Box — Behnken design technique, the experiments are carried out. The input parameters (gas flow rate, voltage, travel speed and wire feed rate) ranges are selected based on the filler wire thickness and base material thickness and the corresponding output variables such as bead width (BW), bead height (BH) and depth of penetration (DP) are measured using optical microscopy. Based on the experimental data, the mathematical models are developed as per regression analysis using Design Expert 7.1 software. An attempt is made to minimize the bead width and bead height and maximize the depth of penetration using genetic algorithm.