The optimal cutting-parameter selection of heavy cutting process in side milling for SUS304 stainless steel

This paper presents an optimal cutting-parameter design of heavy cutting in side milling for SUS304 stainless steel. The orthogonal array with grey-fuzzy logics isapplied to optimize the side milling process with multiple performance characteristics. A grey-fuzzy reasoning grade obtained from the grey-fuzzylogics analysis is used as a performance index to determine the optimal cutting parameters. The selected cutting parameters are spindle speed, feed per tooth,axial depth of cut and radial depth of cut, while the considered performance characteristics are tool life and metal removal rate. The results ofconfirmation experiments reveal that grey-fuzzy logics can effectively acquire an optimal combination of the cutting parameters. Hence, performance in theside milling process for heavy cutting can be significantly improved through this approach.     

Design optimization of cutting parameters for side milling operations with multiple performance characteristics

In this paper, a grey relational analysis is applied to a set of two-stage experiments designed to determine the cutting parameters for optimizing the side milling process with multiple performance characteristics. The cutting parameters to be considered are cutting speed, feed per tooth, axial depth of cut, radial depth of cut, overhang length and flank wear of peripheral cutting edge. L₃₆ and L₉ orthogonal arrays are used in the experiments and lower-the-better is used as a qualitative characteristic to evaluate the results. It is found that using the grey relational analysis coupled with a deliberate design of the two-stage experiments is simple and efficient in determining an optimal combination of the cutting parameters. The results of the confirmation test also show that this new approach can greatly improve the cutting performance of side milling process.     

Selection of cutting parameters in side milling operation using graph theory and matrix approach

This paper presents the selection of cutting parameters of heavy cutting process in side milling using graph theory and matrix approach (GTMA). The multiple attribute decision-making methods are also applied to rank and select the cutting parameters for the given application. The objective is to find the optimized cutting parameters in side milling operation. The considered performance characteristics are tool wear rate and metal removal rate. In GTMA approach, a ??performance suitability index (PSI)?? evaluates and ranks the performance characteristics from the given alternatives. It is registered that the performance, for which the value of PSI is highest, is the best choice for the given application. The index is derived from the graph of performance selection factors. An example is included to illustrate the approach.     

Optimisation for hot turning operations with multiple performance characteristics

This paper presents an investigation on the optimisation and the effect of cutting parameters on multiple performance characteristics (the tool life and the workpiece surface roughness) obtained by hot turning operations. A plan of experiments based on the Taguchi method was designed. M20 sintered carbide as tool and the high manganese steel as workpiece material were used in experiments. The workpiece material heated with liquid petroleum gas flame was machined under different settings of feed rate, depth of cut, cutting speed and workpiece temperature on a lathe. The results showed that cutting speed and feed rate were the dominant variables on multiple cutting performance characteristics. An optimum parameter combination was obtained by using statistical analysis.     

Analysis model of parameters affecting cutting performance in high-speed machining

Further progress in green cutting applications depends on the innovativeness of machine tools, advances in tool development, and, especially, more complex tool and cutting technologies. Therefore, this study analyzes the factors influencing high-speed cutting performance. Grey relational analysis and the Taguchi method are then incorporated in the experimental plan with high-speed milling of AISI H13 tool steel. Experimental results indicate that the contributions of tool grinding precision, geometric angle, and cutting conditions to the multiple quality characteristics of high-speed milling for AISI H13 tool steel are 11.75, 9.80, and 73.11 %, respectively. For rough machining, tool life and metal removal volume are the primary evaluation indicators and cutting parameters should be prioritized, especially cutting speed and feed per tooth. In finish machining, workpiece surface roughness is the primary evaluation indicator. Besides the selection of cutting parameters, the design and grinding of endmill are critical factors, especially the design and grinding of relief angles.     

Optimization of bone drilling parameters using grey-based fuzzy algorithm

In this article a modified algorithm (grey based fuzzy algorithm) is used to optimize multiple performance characteristics in drilling of bone. Experiments have been performed with different cutting conditions using full factorial design. The quality parameters considered are temperature, force and surface roughness. Grey relational analysis (GRA) coupled with fuzzy logic is employed to obtain a grey fuzzy reasoning grade (GFRG) combining all the quality characteristics. The highest GFRG is obtained for the feed rate of 40 mm/min and the speed of 500 rpm and is the optimal level. Analysis of variance (ANOVA) carried out to find the significance of parameters on multiple performance characteristics revealed that the feed rate has the highest contribution on GFRG followed by the spindle speed. The optimum level of the process parameters obtained is validated by the confirmation experiment.     

球头铣刀切削力计算机预报模型的数值仿真

借助建立的铣刀切削力、扭矩和切削功率的计算机预报模型 ,对平前刀面球头铣刀的切削性能进行了数值仿真研究 ;通过分析各种切削参数对切削性能的影响规律 ,获得了不同切削条件下球头铣刀切削力和扭矩的特征和变化趋势     

高锰钢切削加工工艺性能的分析

介绍了高锰钢切削加工工艺性能的特点,加工中常见的不良现象和原因及改善其切削加工工艺性能的主要途径。通过实际测定并结合常用切削加工工艺参数,给出了合理的切削加工工艺参数参考值,有效地解决了高锰钢的高难加工问题。     

Multi-objective optimization of surface roughness and cutting forces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA)

In this paper, a new effective approach, Taguchi grey relational analysis has been applied to experimental results in order to optimize the high-speed turning of Inconel 718 with consideration to multiple performance measures. The approach combines the orthogonal array design of experiments with grey relational analysis. Grey relational theory is adopted to determine the best process parameters that give lower magnitude of cutting forces as well as surface roughness. The response table and the grey relational grade graph for each level of the machining parameters have been established. The parameters: cutting speed, 475?m/min; feed rate, 0.10?mm/rev; depth of cut, 0.50?mm; and CW2 edge geometry have highest grey relational grade and therefore are the optimum parameter values producing better turning performance in terms of cutting forces and surface roughness. Depth of cut shows statistical significance on overall turning performance at 95% confidence interval.     

Analysis and prediction of tool wear, surface roughness and cutting forces in hard turning with CBN tool

The main of the present study is to investigate the effects of process parameters (cutting speed, feed rate and depth of cut) on performance characteristics (tool life, surface roughness and cutting forces) in finish hard turning of AISI 52100 bearing steel with CBN tool. The cutting forces and surface roughness are measured at the end of useful tool life. The combined effects of the process parameters on performance characteristics are investigated using ANOVA. The composite desirability optimization technique associated with the RSM quadratic models is used as multi-objective optimization approach. The results show that feed rate and cutting speed strongly influence surface roughness and tool life. However, the depth of cut exhibits maximum influence on cutting forces. The proposed experimental and statistical approaches bring reliable methodologies to model, to optimize and to improve the hard turning process. They can be extended efficiently to study other machining processes.     

Multi response optimization of wire EDM operations using robust design of experiments

In this present study a multi response optimization method using Taguchi’s robust design approach is proposed for wire electrical discharge machining (WEDM) operations. Experimentation was planned as per Taguchi’s L16 orthogonal array. Each experiment has been performed under different cutting conditions of pulse on time, wire tension, delay time, wire feed speed, and ignition current intensity. Three responses namely material removal rate, surface roughness, and wire wear ratio have been considered for each experiment. The machining parameters are optimized with the multi response characteristics of the material removal rate, surface roughness, and wire wear ratio. Multi response S/N (MRSN) ratio was applied to measure the performance characteristics deviating from the actual value. Analysis of variance (ANOVA) is employed to identify the level of importance of the machining parameters on the multiple performance characteristics considered. Finally experimental confirmation was carried out to identify the effectiveness of this proposed method. A good improvement was obtained.     

OPTIMIZATION STUDIES ON HOLE-MAKING TOOLS FOR HIGH-PERFORMANCE CUTTING AUSTENITIC STAINLESS STEEL

Austenitic stainless steel is a kind of difficult-to-cut material utilized widely in various industry fields. Hole-making tools are the uppermost obstacle of high performance cutting, so the optimizations of tools are imperative. This paper presents respectively the optimal geometrical characteristics and corresponding coating for high performance cutting austenitic stainless steel. The appreciated cutting performance of optimized tools with optimized cutting parameters has also been evaluated completely through experiments. Optimized special drills with point angle 138° and helix angle 38° was decided and TiCN coating was selected as the best coating. However optimized taps had different geometry structures for tapping through holes and blind holes. The former adopted the spiral pointed tap with inclination angle 15 °. The latter was spiral fluted tap with helix angle 34°. In high-performance cutting austenitic stainless steel, the optimized cutting parameters of special drills are 16 m/min and 0.13 mm/rev. The research results will be of great benefit for the development and application of high efficient and precise drills and taps of high performance cutting austenitic stainless steel.     

Multi-response optimization of machining parameters in hot turning using grey analysis

This paper envisages the multi-response optimization of machining parameters in hot turning of stainless steel (type 316) based on Taguchi technique. The workpiece heated with liquid petroleum gas flame burned with oxygen was machined under different parameters, i.e., cutting speed, feed rate, depth of cut, and workpiece temperature on a conventional lathe. The effect of cutting speed, feed rate, depth of cut, and workpiece temperature on surface roughness, tool life, and metal removal rate have been optimized by conducting multi-response analysis. From the grey analysis, a grey relational grade is obtained and based on this value an optimum level of cutting parameters has been identified. Furthermore, using analysis of variance method, significant contributions of process parameters have been determined. Experimental results reveal that feed rate and cutting speed are the dominant variables on multiple performance analysis and can be further improved by the hot turning process.     

Optimisation of machining parameters for hard machining: grey relational theory approach and ANOVA

The present paper deals with experimental investigations carried out for machinability study of hardened steel and to obtain optimum process parameters by grey relational analysis. An orthogonal array, grey relations, grey relational coefficients and analysis of variance (ANOVA) are applied to study the performance characteristics of machining process parameters such as cutting speed, feed, depth of cut and width of cut with consideration of multiple responses, i.e. volume of material removed, surface finish, tool wear and tool life. Tool wear patterns are measured using optical microscope and analysed using scanning electron microscope and X-ray diffraction technique. Chipping and adhesion are main causes of wear. The optimum process parameters are calculated for rough machining and finish machining using grey theory and results are compared with ANOVA.     

PCBN刀具切削堆焊钴基合金的试验研究

采用PCBN刀具对堆焊钴基高温合金层进行切削试验,研究不同的切削用量和刀尖圆弧半径对表面粗糙度和切削力的影响规律,并采用离差分析法对其影响程度进行评估。试验结果及分析表明:切削加工堆焊钴基合金时,切削力和表面粗糙度的部分变化规律有别于传统切削理论,这是因为钴基堆焊合金特有的物理机械性能、堆焊层组织状态、PCBN刀具的性能特点及所选取的几何参数使切削区域材料性能变化和刀具磨损特征不同于传统切削理论所致。试验获得的表面粗糙度值较小,符合以车代磨的加工工艺要求。由离差分析结果可知,进给量对表面粗糙度、主切削力和背向力影响最大,背吃刀量对进给力的影响最大。     

OPTIMIZATION STUDIES ON HOLE-MAKING TOOLS FOR HIGH-PERFORMANCE CUTTING AUSTENITIC STAINLESS STEEL

Austenitic stainless steel is a kind of difficult-to-cut material utilized widely in various industry fields. Hole-making tools are the uppermost obstacle of high performance cutting, so the optimizations of tools are imperative. This paper presents respectively the optimal geometrical characteristics and corresponding coating for high performance cutting austenitic stainless steel. The appreciated cutting performance of optimized tools with optimized cutting parameters has also been evaluated completely through experiments. Optimized special drills with point angle 138° and helix angle 38° was decided and TiCN coating was selected as the best coating. However optimized taps had different geometry structures for tapping through holes and blind holes. The former adopted the spiral pointed tap with inclination angle 15 °. The latter was spiral fluted tap with helix angle 34°. In high-performance cutting austenitic stainless steel, the optimized cutting parameters of special drills are 16 m/min and 0.13 mm/rev. The research results will be of great benefit for the development and application of high efficient and precise drills and taps of high performance cutting austenitic stainless steel.     

High-Speed Machining of Malleable Cast Iron by Various Cutting Tools Coated by Physical Vapor Deposition

The coating material of a tool directly affects the efficiency and cost of machining malleable cast iron.However,the machining adaptability of various coating materials to malleable cast iron has been insufficiently researched.In this paper,turning tests were conducted on cemented carbide tools with different coatings(a thick TiN/TiAlN coating,a thin TiN/TiAlN coating,and a nanocomposite(nc)TiAlSiN coating).All coatings were applied by physical vapor deposi-tion.In a comparative study of chip morphology,cutting force,cutting temperature,specific cutting energy,tool wear,and surface roughness,this study analyzed the cutting characteristics of the tools coated with various materials,and established the relationship between the cutting parameters and machining objectives.The results showed that in malleable cast iron machining,the coating material significantly affects the cutting performance of the tool.Among the three tools,the nc-TiAlSiN-coated carbide tool achieved the minimum cutting force,the lowest cutting tempera-ture,least tool wear,longest tool life,and best surface quality.Moreover,in comparisons between cemented-carbide and compacted-graphite cast iron machined under the same conditions,the wear mechanism of the coated tools was found to depend on the cast iron being machined.Therefore,the performance requirements of a tool depend on multiple factors,and selecting an appropriately coated tool for a particular cast iron material is essential.     

Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method

Wire electrical discharge machining (WEDM) is extensively used in machining of conductive materials when precision is of prime importance. Rough cutting operation in WEDM is treated as a challenging one because improvement of more than one machining performance measures viz. metal removal rate (MRR), surface finish (SF) and cutting width (kerf) are sought to obtain a precision work. Using Taguchi’s parameter design, significant machining parameters affecting the performance measures are identified as discharge current, pulse duration, pulse frequency, wire speed, wire tension, and dielectric flow. It has been observed that a combination of factors for optimization of each performance measure is different. In this study, the relationship between control factors and responses like MRR, SF and kerf are established by means of nonlinear regression analysis, resulting in a valid mathematical model. Finally, genetic algorithm, a popular evolutionary approach, is employed to optimize the wire electrical discharge machining process with multiple objectives. The study demonstrates that the WEDM process parameters can be adjusted to achieve better metal removal rate, surface finish and cutting width simultaneously.     

Effect of work material hardness and cutting parameters on performance of coated carbide tool when turning hardened steel: An optimization approach

In present work performance of coated carbide tool was investigated considering the effect of work material hardness and cutting parameters during turning of hardened AISI 4340 steel at different levels of hardness. The correlations between the cutting parameters and performance measures like cutting forces, surface roughness and tool life, were established by multiple linear regression models. The correlation coefficients found close to 0.9, showed that the developed models are reliable and could be used effectively for predicting the responses within the domain of the cutting parameters. Highly significant parameters were determined by performing an Analysis of Variance (ANOVA). Experimental observations show that higher cutting forces are required for machining harder work material. These cutting forces get affected mostly by depth of cut followed by feed. Cutting speed, feed and depth of cut having an interaction effect on surface roughness. Cutting speed followed by depth of cut become the most influencing factors on tool life; especially in case of harder workpiece. Optimum cutting conditions are determined using response surface methodology (RSM) and the desirability function approach. It was found that, the use of lower feed value, lower depth of cut and by limiting the cutting speed to 235 and 144 m/min; while turning 35 and 45 HRC work material, respectively, ensures minimum cutting forces, surface roughness and better tool life.     

Multi-response optimization of machining parameters on red mud-based aluminum metal matrix composites in turning process

This paper presents the findings of an experimental investigation into the effects of cutting speed, feed rate, depth of cut, and nose radius in computer numerical control (CNC) turning operation performed on red mud-based aluminum metal matrix composites. This paper investigates optimization design of a turning process performed on red mud-based aluminum metal matrix composites. The major performance characteristics selected to evaluate the process are surface roughness, power consumption, and vibration, and the corresponding turning parameters are cutting speed, feed, depth of cut, and nose radius. Taguchi-based grey analysis, which uses grey relational grade as performance index, is specifically adopted to determine the optimal combination of turning parameters. The principal component analysis (PCA) is applied to evaluate the weighting values corresponding to various performance characteristics. L9 orthogonal array design has been used for conducting the experiments. The outcome of confirmation experiments reveals that grey relational analysis coupled with PCA can effectively be used to obtain the optimal combination of turning parameters. Hence, this confirms that the proposed approach in this study can be a useful tool to improve the turning performance of red mud-based aluminum metal matrix composites in CNC turning process.