Multi-criteria end milling parameters optimization of AISI D2 steel using genetic algorithm

This paper focuses on using multi-criteria optimization approach in the end milling machining process of AISI D2 steel. It aims to minimize the cost caused by a poor surface roughness and the electrical energy consumption during machining. A multi-objective cost function was derived based on the energy consumption during machining, and the extra machining needed to improve the surface finish. Three machining parameters have been used to derive the cost function: feed, speed, and depth of cut. Regression analysis was used to model the surface roughness and energy consumption, and the cost function was optimized using a genetic algorithm. The optimal solutions for the feed and speed are found and presented in graphs as functions of extra machining and electrical energy cost. Machine operators can use these graphs to run the milling process under optimal conditions. It is found that the optimal values of the feed and speed decrease as the cost of extra machining increases and the optimal machining condition is achieved at a low value of depth of cut. The multi-criteria optimization approach can be applied to investigate the optimal machining parameters of conventional manufacturing processes such as turning, drilling, grinding, and advanced manufacturing processes such as electrical discharge machining.     

An experimental investigation of affected layers formed in grinding of AISI 52100 steel

A systemic experimental investigation involving scanning electron microscopy, Vickers microhardness tester, X-ray diffraction, three-axis piezoelectric dynamometer, and thermocouple was carried out to analyze the affected layers formed in grinding of AISI 52100 steel. The formation mechanisms and properties of affected layer at different grinding conditions were investigated. It is found that the phase transformation, as well as retained austenite and white layer, can be formed at the grinding temperature below the nominal phase transformation temperature of the workpiece material. Mechanical effect associated with plastic deformation also can influence the white layer formation, and play an important role for the phase transformation of the ground workpiece. Furthermore, higher hardness and residual tensile stress are observed on the ground surface of hardened steel, but it shows residual compressive stress on the ground surface of annealed steel.     

An experimental investigation on micro machining of fine-grained graphite

Industrial applications of the micro milling process require sufficient experimental data from various micro tools. Research has been carried out on micro milling of various engineering materials in the past two decades. However, there is no report in the literature on micro milling of graphite. This paper presents an experimental investigation on micro machinability of micro milling of moulded fine-grained graphite. Full immersion slot milling was conducted using diamond-coated, TiAlN-coated and uncoated tungsten carbide micro end mills with a uniform tool diameter of 0.5 mm. The experiments were carried out on a standard industrial precision machining centre with a high-speed micro machining spindle. Design of experiments (DoE) techniques were applied to design and analysis of the machining process. Surface roughness, surface topography and burrs formation under varying machining conditions were characterized using white light interferometry, SEM and a precision surface profiler. Influence of variation of cutting parameters including cutting speeds, feedrate and axial depth of cut on surface roughness and surface damage was analysed using ANOVA method. The experimental results show that feedrate has the most significant influence on surface roughness for all types of tools, and diamond tools are not sensitive to cutting speed and depth of cut. Surface damage and burrs analysis show that the primary material removal mode is still brittle fracture or partial ductile in the experimental cutting conditions. 3D intricate micro EDM electrodes were fabricated with good dimensional accuracy and surface finishes using optimized machining conditions to demonstrate that micro milling is an ideal process for graphite machining.     

磁力研磨法去毛刺的实验研究

研制了去毛刺实验装置,用有限元法分析了加工间隙磁场分布,实验结果表明利用磁力研磨法能够去除棱边毛刺,并保持适宜的棱边圆角半径。     

Neuro-fuzzy and neural network-based prediction of various responses in electrical discharge machining of AISI D2 steel

In the present research, two neuro-fuzzy models and a neural network model are presented for predictions of material removal rate (MRR), tool wear rate (TWR), and radial overcut (G) in die sinking electrical discharge machining (EDM) process for American Iron and Steel Institute D2 tool steel with copper electrode. The discharge current (I _p), pulse duration (T _on), duty cycle (τ), and voltage (V) are considered as inputs to the network. A full-factorial design was used to conduct the experiments with various levels of I _p, T _on, τ, and V. The analysis of variance results reveal that I _p is the most influencing factor for MRR and G, having the highest degree of contributions of 87.61% and 81.90%, respectively. In case of TWR, T _on has the highest degree of contribution of 46.05% and is the most significant factor. The half of the experimental data set was used to train the networks and was tested for convergence with a different set of data to obtain appropriate number of neurons, epoch, and the fuzzy rule base. The mean square error convergence criteria, both in training and testing, came out very well. The developed models are found to approximate the responses quite accurately. Moreover, the predicted results based on above models have been confirmed with unseen validation set of experiments and are found to be in good agreement with the experimental results. The comparison results reveal that the artificial neural network and the neuro-fuzzy models are comparable in terms of accuracy and speed, and further, the proposed models can be employed successfully in prediction of MRR, TWR, and G of the stochastic and complex EDM process.     

An investigation of surface roughness of burnished AISI 1042 steel

The aim of this study is to analyse the evolution of surface roughness finished by burnishing. Burnishing is done on a surface that was initially turned or turned and then ground.It has been noted that burnishing an AISI 1042 steel offers the best surface quality when using a small feed value. This finishing process improves roughness and introduces compressive residual stresses in the machined surface. So, it can replace grinding in the machining range of the piece.Also, an analytical model has been defined to determine the R_t factor in relation to the feed. Good correlations have been found between the experimental and analytical results.     

Precision radial turning of AISI D2 steel

This paper compares finite element model (FEM) simulations with experimental and analytical findings concerning precision radial turning of AISI D2 steel. FEM machining simulation employs a Lagrangian finite element-based machining model applied to predict cutting and thrust forces, cutting temperature and plastic strain distribution. The results show that the difference between the experimental and simulated cutting force is near 20%, irrespectively of the friction coefficient used in the simulation work (approximately 19.8% for a friction of 0.25% and 18.4% for the Coulomb approach). Concerning the thrust force, differences of about 22.4% when using a friction coefficient of μ?=?0.25 and about 56.9% when using the Coulomb friction coefficient (μ?=?0.378) were found. The maximum cutting temperature obtained using the analytical model is 494.07°C and the difference between experimentation and simulation methods is 15.2% when using a friction coefficient of 0.25 and when using the Coulomb friction only 3.1%. Regarding the plastic strain, the differences between analytical calculations and FEM simulations (for the presented friction values) suggest that the finite element method is capable of predictions with reasonable precision.     

Multi-response optimization of Micro-EDM process parameters on AISI304 steel using TOPSIS

The Technique for order preference by similarity to ideal solution (TOPSIS) method of optimization is used to analyze the process parameters of the micro-Electrical discharge machining (micro-EDM) of an AISI 304 steel with multi-performance characteristics. The Taguchi method of experimental design L27 is performed to obtain the optimal parameters for inputs, including feed rate, current, pulse on time, and gap voltage. Several output responses, such as the material removal rate, electrode wear rate, overcut, taper angle, and circularity at entry and exit points, are analyzed for the optimal conditions. Among all the investigated parameters, feed rate exerts a greater influence on the hole quality. ANOVA is employed to identify the contribution of each experiment. The optimal level of parameter setting is maintained at a feed rate of 4 μm/s, a current of 10 A, a pulse on time of 10 μs, and a gap voltage of 10 V. Scanning electron microscope analysis is conducted to examine the hole quality. The experimental results indicate that the optimal level of the process parameter setting over the overall performance of the micro-EDM is improved through TOPSIS.     

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.     

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.     

Influence of machining parameters on surface roughness in finish cut of WEDM

Surface roughness is significant to the finish cut of wire electrical discharge machining (WEDM). This paper describes the influence of the machining parameters (including pulse duration, discharge current, sustained pulse time, pulse interval time, polarity effect, material and dielectric) on surface roughness in the finish cut of WEDM. Experiments proved that the surface roughness can be improved by decreasing both pulse duration and discharge current. When the pulse energy per discharge is constant, short pulses and long pulses will result in the same surface roughness but dissimilar surface morphology and different material removal rates. The removal rate when a short pulse duration is used is much higher than when the pulse duration is long. Moreover, from the single discharge experiments, we found that a long pulse duration combined with a low peak value could not produce craters on the workpiece surface any more when the pulse energy was reduced to a certain value. However, the condition of short pulse duration with high peak value still could produce clear craters on the workpiece surface. This indicates that a short pulse duration combined with a high peak value can generate better surface roughness, which cannot be achieved with long pulses. In the study, it was also found that reversed polarity machining with the appropriate pulse energy can improve the machined surface roughness somewhat better compared with normal polarity in finish machining, but some copper from the wire electrode is accreted on the machined surface.     

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 experimental investigation on the machining characteristics of microscale end milling

This paper discusses an experimental approach to assess the machining characteristics in microscale end milling operation through a systematic experimentation procedure. Microchannels were machined on brass plates using a carbide end mill of 1?mm diameter to analyze the effect of chip load (feed per tooth) and cutting speed on the surface roughness, specific cutting pressure, and cutting forces during microend milling operation. The tangential and radial components of forces were analyzed with the help of a three-dimensional model using the force signals acquired through KISTLER dynamometer. Feed per tooth and the interaction of cutting speed and chip load were identified as the critical parameters affecting the surface roughness of microchannel. Applying the concept of elastic recovery on the side wall surface of microchannels, the minimum chip thickness during the above micromilling operation was evaluated as 0.97???m, and the result was validated by the drastic increase in specific cutting pressure and erratic behavior of cutting forces below a chip load of 1???m.     

Experimental investigation and economic analysis of surfactant (Span-20) in powder mixed electrical discharge machining (PMEDM) of AISI D2 hardened steel

Abstract

Powder mixed EDM (PMEDM) is recognized as an advanced and innovative technique with enhanced performance and limited drawbacks in comparison to conventional EDM method. This study investigates the effect of powder particle size, various powder concentrations (C_p), and surfactant concentrations (C_s) on the performance of EDM. Since the machining characteristics are highly dependent on the dielectric performances, significant attention has been directed to introduce Cr powder and Span-20 surfactant into the dielectric fluid to achieve higher productivity and enhanced surface integrity. The EDM machining was carried out on AISI D2 hardened steel through ´Plug & Plaý dielectric circulating system attached to the main machine in order to evaluate the machining performances (i.e. MRR, EWR, and R_a). Interestingly, machining performance was improved with combination of Cr powder mixed and span-20 surfactant. By comparing the performance of span-20 surfactant and micro-nano chromium, the result within selected parameters shows that the span-20 surfactant and nano-chromium is the better choice for the EDM of AISI D2 hardened steel. In the machinability studies, the EDM machining of AISI D2 hardened steel by using span-20 surfactant and nano-chromium has exhibited the excellent machining performances, which led to 45.08% MRR enhancement and 68.89% R_a enhancement comparing to micro-chromium powder and span-20 surfactant led to 35.28% MRR and 28.96% R_a. Furthermore, cost analysis revealed that the nano-Cr powder size was approximately 4 times more economical than micro-Cr powder in machining of AISI D2 hardened steel, although the price for 1?kg is quite expensive.     

An experimental investigation on the process parameters influencing machining forces during milling of carbon and glass fiber laminates

Milling is the most feasible machining operation for producing slots and keyways with a well defined and high quality surface. Milling of composite materials is a complex task owing to its heterogeneity and the associated problems such as surface delamination, fiber pullout, burning, fuzzing and surface roughness. The machining process is dependent on the material characteristics and the cutting parameters. An attempt is made in this work to investigate the influencing cutting parameters affecting milling of composite laminates. Carbon and glass fibers were used to fabricate laminates for experimentations. The milling operation was performed with different feed rates, cutting velocity and speed. Numerically controlled vertical machining canter was used to mill slots on the laminates with different cutting speed and feed combinations. A milling tool dynamo meter was used to record the three orthogonal components of the machining force. From the experimental investigations, it was noticed that the machining force increases with increase in speed. For the same feed rate the machining force of GFRP laminates was observed to be very minimal, when compared to machining force of CFRP laminates. It is proposed to perform milling operation with lower feed rate at higher speeds for optimal milling operation.     

An investigation of tool wear in high-speed turning of AISI 4340 steel

A commercially available insert has been used to turn an AISI 4340 steel at speeds placed between 325 and 1000 m/min. The flank wear was measured in connection to cutting time. This is to determine the tool life defined as the usable time that has elapsed before the flank wear has reached the criterion value.It is shown that an increase in cutting speed causes a higher decrease of the time of the second gradual stage of the wear process. This is due to the thin coat layer which is rapidly peeled off when high-speed turning.The investigation included the realization of a wear model in relation to time and to cutting speed. An empirical model has also been developed for tool life determination in connection with cutting speed.On the basis of the results obtained it is possible to set optimal cutting speed to achieve the maximum tool life.     

An experimental investigation of tool wear in electric discharge machining

In this study, the variations of geometrical tool wear characteristics – namely, edge and front wear – and machining performance outputs – namely, workpiece removal rate, tool wear rate, relative wear and workpiece surface roughness – were investigated with varying machining parameters. Experiments were conducted using steel workpieces and round copper tools with a kerosene dielectric under different dielectric flushing conditions (injection, suction and static), discharge currents and pulse durations. The experiments have shown that machining parameters and dielectric flushing conditions had a large effect on geometric tool wear characteristics and machining performance outputs. Additionally, published research on tool wear is presented in detail in this study.     

An investigation on wear mechanism of high-speed turning of free-cutting steel AISI 1215 using uncoated and multi-layer coated tools

AISI 1215 is a new kind of green and non-toxic free-cutting steel with minimum environmental pollution and excellent machinability, which receives wide promotion, investigation, and application in manufacturing industries. In machining of AISI 1215 steel, tool wear has a close relation with the presence of manganese sulfide lubricant zone formed on the tool surface. In this work, with the aid of cutting temperature and tool Von Mises stress simulations, tool wear analysis on the uncoated and multi-layer (Al₂O₃/TiCN) coated carbide tools was performed in high-speed turning operation. Wear pattern and wear mechanisms were studied through the experimental results. The main findings showed that the uncoated tool suffered high cutting temperature and severe tool wear and was not conducive to form a manganese sulfide lubricant zone in the turning operation. In contrast, the multi-layer coated tool could form a manganese sulfide lubricant zone on the chip–tool contact area. The beneficial roles of the manganese sulfide lubricant zone formed on the coated tool surface can be summarized as lubrication and diffusion blocking. The main wear mechanisms of the uncoated tool were crater wear, oxidation wear, adhesive wear, and abrasive wear, whereas for the multi-layer coated tool, they were crater wear, adhesive wear, and abrasive wear.     

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。