Optimal Combination Of Process Parameters Research Articles

Multiobjective Optimization of Heat-Treated Copper Tool Electrode on EMM Process Using Artificial Bee Colony (ABC) Algorithm.

Electrochemical micromachining (EMM) is a plausible method for manufacturing high accuracy and precision microscale components in a broad range of materials. EMM is commonly utilized to manufacture turbine blades for automobiles and aircrafts. In this present study, the EMM process was performed with a heat-treated copper tool electrode on aluminum 8011 alloy. The process parameters such as voltage, concentration of electrolyte, frequency, and duty factor were varied to analyze the effect of a heat-treated electrode on material removal rate (MRR), overcut, conicity, and circularity. It was observed that high MRR was obtained with lower overcut with an annealed electrode. The better conicity and circularity were obtained with a quenched electrode compared to other heat-treated and untreated tool electrodes. The artificial bee’s colony (ABC) algorithm was used to identify the optimum parameters and, finally, the confirmation test was carried out to evaluate the error difference on the machining process. The optimum combination of input process parameters found using TOPSIS and ABC algorithm for the EMM process are voltage (14 V), electrolyte concentration (30 g/L), frequency (60 Hz), and duty cycle (33%) for the annealed tool electrode and voltage (14 V), electrolyte concentration (20 g/L), frequency (70 Hz), and duty cycle (33%) for the quenched tool electrode. It was confirmed that 95% of accurate response values were proven under the optimum parameter combination.

Analysis of the Effect of Tool Geometry and Hole Quality on Drilling Carbon-Fibre Reinforced Polymer Composite Using ANSYS

This study focused on the analysis of the effect of tool geometry and hole quality on drilling carbon-fibre reinforced polymer (CFRP) composite using ANSYS. The experiment was conducted on computer numerical control machine (CNC) using high speed steel (HSS) twist drill bit and HSS-COBALT drill type. Taguchi L9 orthogonal array was used for the optimization analysis. Analysis of variance (ANOVA) was employed to determine the most significant control factors affecting the drilling process. The machining parameters involving tool type, point angle, spindle speed and feed rate were selected as control factors. While the dependable variables on workpiece were cutting force, stress and strain. The main interaction effect of the input variables on the predicted responses was investigated. The ANOVA/F-test results for cutting force with the contribution of each machining parameters revealed that the cutting speed was the dominant factor influencing cutting force developed with a contribution of 57 percent, The second factor affecting cutting force developed was point angle with a contribution of 5.7 percent, while f eed rate had the least effect on cutting force developed where its contribution of 1.4 percent. Based on the results observed, the optimal machining parameters that produced minimum stress was observed with HSSCOBALT drill at 118 degrees of point angle, 300 mm/min of feed and 500 rpm of speed. Also from Taguchi results, the optimal combination of process parameters to obtain maximum strain with HSS drill, 135 degrees of point angle, and 300 mm/min of feed and 1500 rpm of speed produced the optimal drilling condition for CFRC polymer within the scope of this research work.

A Multi-Objectives Genetic Algorithm Based Predictive Model and Strategy Optimization during SLM Process.

Selective laser melting (SLM) process was optimized in this work using multi-objectives genetic algorithm. Process parameters involved in the printing process have an obvious impact on the quality of the printed parts. As the relationship between process parameters and the quality of different parts are complex, it is quite essential to study the effect of process parameter combination. In this work, the impact of four main process parameters, including defocusing amount, laser power, scan speed and layer thickness, were studied on overhanging surface quality of the parts with different inner structures. A multiple-factor and multiple-level experiment was conducted to establish a prediction model using regression analysis while multi-objective genetic algorithm was also employed here to improve the overhanging surface quality of parts with different inner shapes accordingly. The optimized process parameter combination was also used to print inner structure parts and compared with the prediction results to verify the model we have obtained before. The prediction results revealed that sinking distance and roughness value of the overhanging surface on a square-shape inner structure can reduce to 0.017 mm and 9.0 μm under the optimal process parameters combination, while the sinking distance and roughness value of the overhanging surface on a circle-shape inner structure can decrease to 0.014 mm and 10.7 μm under the optimal process parameters combination respectively. The testing results showed that the error rates of the prediction results were all within 10% in spite of random powder bonding in the printing process, which further proved the reliability of the previous results.

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy.

Nitinol-shape memory alloys (SMAs) are widely preferred for applications of automobile, biomedical, aerospace, robotics, and other industrial area. Therefore, precise machining of Nitinol SMA plays a vital role in achieving better surface roughness, higher productivity and geometrical accuracy for the manufacturing of devices. Wire electric discharge machining (WEDM) has proven to be an appropriate technique for machining nitinol shape memory alloy (SMA). The present study investigated the influence of near-dry WEDM technique to reduce the environmental impact from wet WEDM. A parametric optimization was carried out with the consideration of design variables of current, pulse-on-time (Ton), and pulse-off-time (Toff) and their effect were studied on output characteristics of material removal rate (MRR), and surface roughness (SR) for near-dry WEDM of nitinol SMA. ANOVA was carried out for MRR, and SR using statistical analysis to investigate the impact of design variables on response measures. ANOVA results depicted the significance of the developed quadratic model for both MRR and SR. Current, and Ton were found to be major contributors on the response value of MRR, and SR, respectively. A teaching–learning-based optimization (TLBO) algorithm was employed to find the optimal combination of process parameters. Single-response optimization has yielded a maximum MRR of 1.114 mm3/s at Ton of 95 µs, Toff of 9 µs, current of 6 A. Least SR was obtained at Ton of 35 µs, Toff of 27 µs, current of 2 A with a predicted value of 2.81 µm. Near-dry WEDM process yielded an 8.94% reduction in MRR in comparison with wet-WEDM, while the performance of SR has been substantially improved by 41.56%. As per the obtained results from SEM micrographs, low viscosity, reduced thermal energy at IEG, and improved flushing of eroded material for air-mist mixture during NDWEDM has provided better surface morphology over the wet-WEDM process in terms of reduction in surface defects and better surface quality of nitinol SMA. Thus, for obtaining the better surface quality with reduced surface defects, near-dry WEDM process is largely suitable.

The effect of process parameters and characterization for the laser cladding of cBN based composite clad over the Ti6Al4V alloy

In the present study, a metal matrix composite of nitride, boride, and oxide layer over the Ti6Al4V substrate has been formed by using high-quality reinforcement like cBN, TiO2, and Ti6Al4V. Response surface methodology (RSM) has been successfully implemented to investigate the effect of process parameters (laser power, scanning speed, and shielding gas flow rate) on the responses like clad layer thickness and micro-hardness value of the cladded part. Statistical analysis shows that laser power and scanning speed significantly influence layer thickness and microhardness. Further considering the optimal combination of process parameters, cladded surfaces with different percentage compositions of reinforcement are characterized. The clad shows different microstructures like needles, cylindrical rods, and short-length dendritic. These confirm the formation of a metal matrix composites of nitrides and borides (TiN, TiAlN, AlN, and TiB2) as the main constructive phase of the clad. Further analyzing the binding energy of these phases through XPS, the formation of the compounds exhibits higher intensity. These enhance the hardness as well as wear resistance properties of the clad. The coefficient of friction in the cladded surfaces is less than the base material due to anti-wear chemical compounds like boride and nitride. However, spalling craters and wear debris are found in cladded samples.

Enhancing the machinability of SKD61 die steel in power-mixed EDM process with TGRA-based multi criteria decision making

Abstract In the current context, an attempt is being made to improve the electrical discharge machining (EDM) process by using powder particles in a suitable combination. To improve the quality of such procedures, the process parameters should be optimized. The present study proposes to utilize Taguchi–Grey relational analysis to discover the optimal combination of process parameters for SKD61 die steel specimens using titanium powder-mixed EDM (PMEDM). Among the machining parameters chosen, the optimal combination of current (3 A), pulse on-time (37 μs), pulse off-time (37 μs), and powder concentration (4 g/L) was determined experimentally. Due to its relevance in spark energy production, peak current is a more significant factor in PMEDM processes. A superior surface topography was obtained with increased microhardness and fewer microfractures over machined specimens with optimal process parameter in PMEDM. The titanium particles can effectively enhance the surface performance measures during PMEDM-based machining owing to tiny craters and pores with better lubrication.

Simulation Analysis of Multi-Physical Field Coupling and Parameter Optimization of ECM Miniature Bearing Outer Ring Based on the Gas-Liquid Two-Phase Turbulent Flow Model.

Electrochemical machining (ECM) is an essential method for machining miniature bearing outer rings on the high-temperature-resistant nickel-based alloy GH4169. However, the influence of electrolyte temperature distribution and bubble rate distribution on electrolyte conductivity in the ECM area could not be fully considered, resulting in the simulation model not being able to accurately predict the machining accuracy of the outer ring of the miniature bearing, making it challenging to model and predict the optimal process parameters. In this paper, a multiphysics field coupled simulation model of electric, flow, and temperature fields during the ECM of the miniature bearing outer ring is established based on the gas–liquid two-phase turbulent flow model. The simulation analyzed the distribution of electrolyte temperature, bubble rate, flow rate, and current density in the machining area, and the profile change of the outer ring of the miniature bearing during the machining process. The analysis of variance and significance of machining voltage, electrolyte concentration, electrolyte inlet flow rate, and interaction on the mean error of the ECM miniature bearing outer rings was derived from the central composite design. The regression equation between the average error and the process parameters was established, and the optimal combination of process parameters for the average error was predicted, i.e., the minimum value of 0.014 mm could be achieved under the conditions of a machining voltage of 16.20 V, an electrolyte concentration of 9.29%, and an electrolyte inlet flow rate of 11.84 m/s. This is important to improve the machining accuracy of the outer ring of the ECM miniature bearing.

Optimization of Vacuum Brazing Process Parameters in Ti-6Al-4V Alloy

In this study, the optimal parameters of the vacuum brazing titanium alloy Ti-6Al-4V with TiCuNi filler (30 μm-thick metal foil) were investigated by the Taguchi method. The microstructures, microhardness, and fractographs of the titanium brazed joints produced by these optimal parameters were also analyzed. The results of this study demonstrate that for the best tensile strength, the optimal combination of process parameters is: 890 °C soaking temperature, 60 min soaking time, 975 °C brazing temperature, and 45 min brazing time. The tensile strength obtained by welding with the optimal parameters was found to be 1265 MPa. A small error of 0.24% between experimental and predicted values confirmed the validity of the combined optimized parameters. Finally, from the means of variance analysis (ANOVA), out of the four factors, the highest contribution to the optimal parameters was found to be the brazing time, accounting for 47.3%. The base material of vacuum brazing (VB) weldment is mainly composed of white granular α titanium, slender β titanium, and layered structures that are interlaced by α and β. The weld bead, composed of Ti-15Cu-15Ni, contains many slender needle-shaped Widmanstätten structures. This structure is associated with higher strength and lower ductility. The weld bead hardness of the vacuum brazed parts is higher than that of laser beam weldment and gas tungsten arc weldment. This study demonstrates the feasibility of the Taguchi method for obtaining the optimal process parameters of titanium vacuum brazed joints.

Experimental investigation of a novel magnetorheological process based on three revolving curved tip tools for finishing of mild steel

High-quality surface of the cylindrical workpieces would have to be very precise when used in automobile industries, vane pumps, turbines, gears, mild steel dies and punches for plastic industries. The magnetorheological finishing process based on three revolving curved tip tools has been developed for external cylindrical components to address the above issues. Three electromagnetics tools have been used in this magnetorheological method that can move radially inwards or outwards according to the external diameter of the workpiece. During finishing, the workpiece rotates in the anti-clockwise direction, and three curved tip tools revolve around the workpiece in a clockwise direction resulting in more interaction between the workpiece and active abrasive particles. Reciprocating movement is also provided to the workpiece that helps to produce the axial force on the active abrasive particles. The proposed method has been applied to a mild steel shaft to investigate the surface finish of its external surface. Response surface methodology (RSM) has been used to plan and analyse the impacts of different process factors on the percentage change in surface roughness value of the finished surface of the mild steel stepped cylindrical shaft. The optimal combination of process parameters is magnetising current 3.4A, revolving speed of tools 26 rpm, the rotational speed of workpiece 440 rpm, and transverse speed of workpiece 20 cm/min, which shows the maximum percentage change in the surface roughness value. Confirmation experiments have been performed at optimal combination. The lowest Ra value of 85 nm (nanometre) has been achieved from the initial value of 410 nm (nanometre) in the finishing duration of 90 min. The roughness profiles, scanning electron microscopy (SEM) test and reflection test show that the current finishing process can meet high standards for surface quality that aren't possible with conventional methods.

Microstructure, hardness, and wear properties of AA6061/WC nanocomposite fabricated by friction stir processing

Friction stir processing (FSP) is a solid-state microstructural modification technique that has recently become an effective tool to refine microstructures and improve the mechanical properties of metals. In the current study, optimization of FSP parameters, including tool rotational speed, transverse feed, number of passes, and tungsten carbide (WC) nanoparticle volume fractions on mechanical and wear properties of the fabricated AA6061/WC nanocomposite was studied. Optical microscopy and scanning electron microscopy are used for microstructural observations. The process parameters are optimized using the Taguchi technique for single responses towards microhardness and weight loss and the Desirability approach for both responses. The percentage contribution of process parameters is estimated using analysis of variance. The microstructure observation shows that the proper selection of FSP parameters leads to a homogeneous dispersion of the WC particles throughout the matrix, thereby producing a defect-free AA6061/WC nanocomposite without voids. Also, the severe plastic deformation and heat generation during FSP cause the breaking of coarse particles, WC particles, and porous holes and create an ultrafine grain-sized structure via dynamic recrystallization. The results indicated that the microhardness value of the processed composite was found to be 144 VHN, which is 39.81% higher than that of the base metal. Also, the weight loss of all samples decreased as compared to the base metal. Also, it can be observed that the number of passes is the most significant factor for microhardness, with a 40.1% contribution, and for minimum weight loss, the volume fraction is the most significant factor, with a 56.94% contribution. The optimum process parameter combination was found to be 1800 rpm rotation speed, 120 mm/min of transverse feed, 6% volume fraction, and 3 passes that resulted in obtaining optimum values for micro hardness and weight loss. The surface composite developed in this research is considered a suitable material for applications demanding lightweight and enhanced surface properties, including automotive, aerospace, marine, defense, and transportation industries.

Effects of Process Parameters on the Relative Density and Properties of CuCrZr Alloy Produced by Selective Laser Melting

CuCrZr alloy has the advantages of good electrical conductivity, thermal conductivity, high hardness, crack resistance and high softening temperature. It is extensively used in important fields such as rail transit, aerospace, thermonuclear fusion and electronic information. Due to its high melting point, reflectivity, thermal conductivity, etc., it is more difficult to manufacture by selective laser melting (SLM). In this work, the effect of SLM process parameters on the characteristics of CuCrZr samples, such as relative density, hardness and tensile properties, has been investigated using orthogonal experiment method. The experimental results show that laser power is the main factor affecting the properties of the alloy. The tensile strength of the alloy increases with an increase in laser power; it first increases and then decreases with an increase in scanning speed. The optimal combination of process parameters in this paper is as follows: laser power is 240 W, scanning speed is 750 mm/s and scanning spacing is 0.07 mm. The relative density, ultimate tensile strength and hardness of the alloy fabricated by best SLM process parameters was 98.79%, 347 MPa, 133.9 HV, respectively.

A MULTI-OBJECTIVE GREY RELATIONAL APPROACH AND REGRESSION ANALYSIS ON OPTIMIZATION OF DRILLING PROCESS PARAMETERS FOR GLARE FIBER METAL LAMINATES

Fiber metal laminates (FML) are used in outer covering of the fuselage skin structure. The thrust force and the torque generated during drilling process affect the quality of the holes on the structure. The magnitude of cutting forces is controlled by optimizing the drilling process parameters. In this study, the influence of drilling parameters such as spindle speed, feed rate and the weight percentage of layered double hydroxides (LDH) in the binder epoxy on the thrust force and torque during drilling operation was studied. The experiments were designed based on Taguchi’s L9 orthogonal array. The Gray Relational Analysis was used as multi-objective optimization tool for finding the optimal combination of process parameters. The spindle speed was identified as the most influencing process parameter to affect the drill quality in the FMLs. SEM images taken on the drilled specimens for the best and worst input parameter settings were compared and discussed. The regression models were generated to predict the output response values within the range of actual experiments.

Prediction and optimization of dross formation in laser cutting of electrical steel sheet in different environments

Dross formation in laser cutting of electrical steel sheet in different environments, namely oil, alcohol, and air, was predicted and optimized using a deep neural network (DNN) and an improved grey wolf optimizer (I-GWO), respectively. Analyses using random forest method and response surface method showed that the cutting environment, laser power, pulse frequency, and cutting speed had a significant influence on the dross formation. In addition, cutting in oil leads to less dross formation than in alcohol and air. A stacked autoencoder method combined with a multi-objective grey wolf optimizer was employed to generate a pre-trained DNN, followed by a fine-tuning process to obtain the final DNN. The I-GWO was used to determine the optimal combination of process parameters for minimum dross formation. The DNN model proved its efficacy by showing very low values of mean absolute percentage error and very high values of absolute fraction of variation for the training, validation, and testing datasets. Moreover, the accuracy of the developed DNN model was higher than that of other artificial intelligence based methods, namely random vector functional link and support vector machine for regression, as evaluated by nine statistical criteria. The predicted optimal process parameters by the DNN and I-GWO algorithms were verified by validation experiments in which the minimum dross formation was generated.

Pack Siliconizing Optimization of AISI D2 Tool Steel

The paper describes the pack siliconizing optimization procedure for AISI D2 tool steel. Pack siliconizing was performed by employing different treating temperatures (falling in the range 650–950 °C) and times (falling in the range 2–4 h). The siliconizing atmosphere was obtained through silicon (at 12 wt.%) with the addition of different percentages of NH4Cl (falling in the range 0.5–1 wt.%), Al2O3 was used as halide activator. The coatings’ phases evolution was analyzed through X-ray diffraction; the coatings’ thickness was measured through scanning electron microscopy observations of the cross section of the samples; the mechanical properties were evaluated through micro hardness measurements. The results showed that the coatings’ thickness and hardness increase as the treating time and temperature as well as the halide activator percentage increase. The coating procedure optimization was performed by employing the response surface methodology based on Box-Behnken method. The results of the optimization procedure led to the of the optimal combination of processing parameters: 1 wt.% of halide activator, 3.575 holding time, 950 °C in temperature.

Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm

To obtain the optimal processing parameters of ultrasonic roll extrusion, 42CrMo bearing steel was taken as the research object, and the orthogonal test method was used to design an ultrasonic roll extrusion experiment with spindle speed, feed speed, static pressure and amplitude as parameters. Based on the orthogonal test data, the prediction models of surface roughness, surface residual stress and surface hardness were established by a multiple regression method, and the reliability of the model was verified. An algorithm combining SPEA2 and the shift density estimation strategy (SPEA2SDE) was introduced. The performance of the SPEA2SDE algorithm, NSGA II algorithm and SPEA2 algorithm is tested and compared on a three-dimensional test function set to verify its effectiveness. The SPEA2SDE algorithm are used to solve the multi-objective optimization model to obtain the optimal combination of processing parameters, and the ultrasonic roll extrusion experiment is carried out. The research results show that the surface roughness, surface residual stress and surface hardness optimized by the SPEA2SDE algorithm are in good agreement with the experimental values, and the average error is controlled within 10%, which shows that the algorithm can achieve high precision. It can effectively solve the multi-objective optimization problem of ultrasonic roll extrusion process parameters and can be used to guide actual production machining.

The effect of process parameters on chemical mechanical polishing of quartz glass

The effects of polishing pressure, polishing speed and pH value of the polishing slurry on the chemical activity of quartz glass, the material removal rate (MRR) and surface roughness (Ra) of the workpiece were studied. Using MRR and Ra as evaluation indexes, three factors and four levels of the orthogonal test were used to perform chemical mechanical polishing on quartz glass. By measuring the contact angle between the polishing slurry and workpiece, the influence of different polishing slurries on the chemical activity of quartz glass surface was studied. The processing mechanism of CMP quartz glass was analyzed. The order of important factors affecting MRR of quartz glass was: pressure [Formula: see text] rotation speed [Formula: see text] pH value; the order of significant factors affecting Ra of quartz glass was: pressure [Formula: see text] pH value [Formula: see text] rotation speed. The optimum polishing process parameter combination of the MRR was: pressure 27.58 kPa, rotation speed 85 rpm, pH value 12; the optimum polishing process parameter combination of the Ra was: pressure 13.79 kPa, rotation speed 85 rpm, pH value 12. The MRR and Ra of the workpiece are evaluated from the mechanical action of pressure and speed and the chemical action of polishing slurry on the workpiece. The results proved that the effect of the alkaline polishing solution on MRR and Ra of quartz glass is more significant than that of the acidic polishing slurry.

Effect of friction stir processing parameters on producing AA6061/ tungsten carbide nanocomposite

Friction stir processing (FSP) is a modern manufacturing strategy for improving the surface characteristics of materials by modifying their surface via localized plastic deformation. This research focuses on optimization process parameters for tungsten carbide-reinforced 6061 aluminum alloy surface composite using FSP. The effect of the process parameters including tool rotational speed, transverse feed, number of passes, and tungsten carbide particles volume fractions, on ultimate tensile strength (UTS) and grain size of fabricated AA6061/WC surface nanocomposites are investigated. For four factors and three levels, the L27 Taguchi technique is used to formulate the experimental design. The analysis of variance (ANOVA) is used to determine the significance and the percentage contribution of each parameter. The desirability approach is used to optimize the process parameters in terms of tensile strength and average grain size. The results indicate that the proper selection of FSP parameters results in a homogeneous distribution of the WC particles throughout the matrix thereby producing a defect-free AA6061/WC nanocomposite without voids. Also, the severe plastic deformation and heat generation during FSP causes the breaking of coarse particles, WC particles, elimination of porous holes and creates an ultrafine grain-sized structure via dynamic recrystallization. Furthermore, it was concluded that the transverse feed is the most significant factor for ultimate tensile strength with 40.1% contribution whereas the number of passes is the most significant factor for grain size with a 34.7% contribution. The optimum combination of the current process parameters is found to be 1800 rpm rotation speed, 120 mm/min transverse feed, 4.3636% volume fraction, and 3- pass for optimum values of UTS and grain size. The surface composite developed in this work is considered appropriate material for applications requiring lightweight and improved surface properties, such as aerospace, automotive, marine, defense and transportation industries.

Parameter optimization of a biodegradable agricultural film manufactured with wheat straw fiber

Straw fiber mulch film is a promising alternative to petroleum-based plastic mulching film. The optimal combination of process parameters during the manufacturing process of the wheat straw fiber-based plant fiber film (hereinafter referred to as film), was studied via a five-factor and five-level central composite design methodology. Response surface methodology was used to analyze the effects of sizing agent content, wet strength agent mass fraction, basis weight, KP pulp mixing ratio, and beating degree of wheat straw fiber on the dry tensile index, wet tensile index, and degradation time. The optimal parameters were as follows: a sizing agent content of 2.0%, a wet strength agent mass fraction of 60%, a beating degree of wheat straw fiber of 60 °SR, a basis weight of 54.6 to 60.8 g/m2, and a KP pulp mixing ratio of 37.6% to 44.7%. These parameters achieved the desired physical properties, i.e., a degradation time of 55 to 65 d, a dry tensile index of 10 to 12 N·m/g, and a wet tensile index 3.5 to 5.5 N·m/g. With the optimal manufacturing parameters, straw mulch film would meet the demands for agriculture.

Optimization of Electrodeposited Ni-Cr Composite Coatings by using Taguchi Design and Grey Relational Method

In this investigation, the Nickel (Ni) – Chromium (Cr) composite deposits was developed from conductive type nickel plating bath through electrodeposition technique. The Cr particles concentration in bath were taken in three different proportions such as 10 g/l,20 g/l and 30 g/l and got deposited on the Ni plate. The design of experiment technique, L27 orthogonal array of Taguchi method was employed for conducting experiments with different combination of parameters and its level. The parameters taken into consideration were current density level, pH range, bath temperature, Cr concentration in bath and stirrer speed. The experiment includes the measurement of micro hardness, area fraction of Cr, mass of deposit and coating thickness of coated samples with variable input parameters. The main effects of process parameters and their influences on the responses were analyzed. The outcomes shows that Cr concentration in bath and pH range are the most significant parameters for better enhanced responses measured. Microstructure examinations were conducted to analyze Cr deposition in prepared Ni plates using optical metallurgical microscope, scanning electron microscope (SEM) micro images and Energy Dispersive X-Ray (EDX) spectroscopy studies. Furthermore, the decision-making procedure was carried out for maximization of multi-performance measured responses using grey relational analysis (GRA). The optimized plating parameters levels are found to be 4 A/dm2 for Current density, 2.5 for pH, 45˚C for bath temperature, 30 g/l for bath concentration and 300 rpm for agitation speed to have the maximum micro hardness of 1037 HV, 370 mg of mass of deposit, 42% of Cr particle area fractions and 112 µm of coating thickness. Subsequently the obtained optimal combination of process parameters was validated through confirmation experiment. The results shows that the confirmation test responses are well associated with predicted response values on the Ni-Cr coatings.

Research on quality control of precision machining straight internal gear by abrasive flow based on large eddy simulation

Traditional finishing technology is difficult to realize the precision machining of complex geometric parts. Abrasive flow machining technology solves this problem well. Taking the spur internal gear as the research object, the wall shear force, static pressure, dynamic pressure, and abrasive velocity vector of the internal channel of the straight internal gear under different inlet velocity, abrasive concentration, and abrasive particle size are analyzed by using the large eddy simulation method, and the action law of different parameters on the machining of straight internal gear by solid–liquid two-phase abrasive flow is discussed. At the same time, the orthogonal test was carried out. The results show that the solid–liquid two-phase abrasive flow machining technology can effectively remove the burrs, pits, and bulges on the tooth surface of spur internal gear, reduce the tooth surface roughness, and improve the surface quality. The optimal combination of processing parameters and the primary and secondary order of various factors affecting processing are obtained by range analysis and analysis of variance. The regression equation is constructed by regression analysis to verify the effectiveness and accuracy of the model, which provides theoretical support and data reference for actual processing and production.