scholarly journals Multi-Objective Parameter Optimization for Disc Milling Process of Titanium Alloy Blisk Channels

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 173
Author(s):  
Zhishan Li ◽  
Yaoyao Shi
Keyword(s):  
Residual Stress ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Milling Process ◽  
Cutter Life ◽  
Stress Layer ◽  
Grey Relational ◽  
Optimal Process Parameter

The blisk has been widely used in modern high performance aero-engines of high thrust-weight ratio. Disc milling process provides a reliable way to improve the efficiency of the blisk milling. The process parameters of disc milling have crucial effects on the milling efficiency and physical property of blisk. In this paper, material removal rate, cutter life and thickness of residual stress layer are regarded as optimization targets the key process parameters such as spindle speed, cutting depth and feed speed are optimized. Based on the grey relational analysis, the multi-objective optimization problem is transformed into a single objective optimization problem. At the same time, the problem of non-symmetry influence of key process parameters on optimization targets can be solved. And the influence weight of material removal rate, cutter life and thickness of residual stress layer on the grey relational grade (GRG) are calculated according to principal component analysis. The second order prediction model of GRA is developed by response surface method. On the basis of verifying the accuracy of the model, the influence mechanism of the process parameters coupling on the gray correlation degree is analyzed the optimal process parameter combination is obtained as spindle speed with 81.92 rpm, cutting depth with 5.88 mm and feed rate with 66.0823 mm/min. The experimental research show that the optimal process parameter combination can effectively improve the material removal rate and cutter life and reduce the thickness of residual stress layer.

Optimization by Grey Relational Analysis of EDM Parameters on Machining Ti-6Al-4V

2010 ◽  
Vol 139-141 ◽  
pp. 540-544 ◽  
Author(s):  
Zhi Ping Xie ◽  
Ji Ming Zheng ◽  
Bian Li Quan
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Removal Rate ◽  
Electrode Wear ◽  
Relational Analysis ◽  
Wear Ratio ◽  
Grey Relational

In this paper, parameter optimization of the electrical discharge machining process to Ti–6Al–4V alloy considering the multiple responses using the Taguchi method and grey relational analysis is reported. The multi-response optimization of the process parameters are material removal rate (MRR) and electrode wear rate (EWR). The machining parameters including discharge current, voltage, pulse on time and duty factor. Experiment based on the orthogonal array, The optimized process parameters simultaneously leading to a lower electrode wear ratio and higher material removal rate are then verified through a confirmation experiment. The experimental result for the optimal setting shows that there is considerable improvement in the process. The validation experiments show an improved electrode wear ratio of 2.8%, material removal rate of 45.8% when the Taguchi method and grey relational analysis are used.

scholarly journals An integrated approach for the modelling of silicon carbide components laser milling process

2021 ◽  
Author(s):  
Claudio Leone ◽  
Silvio Genna ◽  
Vincenzo Tagliaferri
Keyword(s):  
Silicon Carbide ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Integrated Approach ◽  
Milling Process ◽  
Roughness Parameters ◽  
Laser Milling ◽  
Pulsed Fiber Laser

AbstractThe paper deals with characterisation and modelling of laser milling process on silicon carbide hard ceramic. To this end, a Yb:YAG pulsed fiber laser was adopted to mill silicon carbide bars. Square pockets, 5×5 mm2 in plane dimension, were machined at the maximum nominal average power (30W), under different laser process parameters: pulse frequency, scan speed, hatching distance, repetitions and scanning strategy. After machining, the achieved depth and the roughness parameters were measured by way of digital microscopy and 3D surface profiling, respectively. In addition, the material removal rate was calculated as the ratio between the removed volume/process time. Analysis of variance (ANOVA) was adopted to assess the effect of the process parameters on the achieved depth, the material removal rate (MRR) and roughness parameters, while response surface methodology (RSM) and artificial neuronal networks (ANNs) were adopted to model the process behaviours. Results show that both RSM and ANNs fault in MRR and RSm roughness parameters modelling. Thus, an integrated approach was developed to overcome the issue; the approach is based on the use of the RSM model to obtain a hybrid Training dataset for the ANNs. The results show that the approach can allow improvement in model accuracy.

scholarly journals An Integrated Approach for the Modelling of Silicon Carbide Components Laser Milling Process

2021 ◽  
Author(s):  
Claudio Leone ◽  
Silvio Genna ◽  
Vincenzo Tagliaferri
Keyword(s):  
Silicon Carbide ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Integrated Approach ◽  
Milling Process ◽  
Roughness Parameters ◽  
Laser Milling ◽  
Pulsed Fiber Laser

Abstract The paper deals with characterisation and modelling of laser milling process on Silicon Carbide hard ceramic. To this end, a Yb:YAG pulsed fiber laser was adopted to mill Silicon Carbide bars. Square pockets, 5x5 mm2 in plane dimension, were machined at the maximum nominal average power (30W), under different laser process parameters: pulse frequency, scan speed, hatching distance, repetitions and scanning strategy. After machining, the achieved depth and the roughness parameters were measured by way of digital microscopy and 3D surface profiling, respectively. In addition, the material removal rate was calculated as the ratio between the removed volume/process time. ANalysis Of VAriance (ANOVA) was adopted to assess the effect of the process parameters on the achieved depth, the material removal rate (MRR) and roughness parameters, while Response Surface Methodology (RSM) and Artificial Neuronal Networks (ANNs) were adopted to model the process behaviours. Results show that both RSM and ANNs fault in MRR and RSm roughness parameters modelling. Thus, an integrated approach was developed to overcome the issue; the approach is based on the use of the RSM model to obtain a hybrid Training dataset for the ANNs. The results show that the approach can allow improvement in model accuracy.

scholarly journals Technological Parameter Optimization of Disc-Milling Grooving of Titanium Alloy Based on Grey Correlation Degree

2018 ◽  
Vol 36 (1) ◽  
pp. 139-148
Author(s):  
Zhishan Li ◽  
Yaoyao Shi ◽  
Hongmin Xin ◽  
Tao Zhao ◽  
Cheng Yang
Keyword(s):  
Residual Stress ◽  
Tool Life ◽  
Material Removal Rate ◽  
Material Removal ◽  
Technological Parameter ◽  
Removal Rate ◽  
Grey Correlation ◽  
Correlation Degree ◽  
Grey Correlation Degree ◽  
Stress Layer

In present paper, aim to some problems such as big material removal rate, serious tool wear and obvious plastic deformation during disc-milling grooving, the orthogonal experiment with three factors and three levels was designed. First, the multi-objective optimization was converted to single-objective optimization based on grey correlation analysis, the influence weight of material removal rate, tool life and the depth of residual stress layer on grey correlation degree was determined via principal component analysis. Second, by means of regression analysis of experiment data, the prediction model of grey correlation degree and technological parameters was developed. Accordingly, the variation of material removal rate, tool life, the depth of residual stress layer and grey correlation degree resulted from the various technological parameter were studied. Further, the optimization scheme of technological parameter was put forward. Finally, the technological parameters were optimized with response surface methodology. And then, the disc-milling grooving experiment was carried out. The experiment results showed that material removal rate can be improved significantly under the condition of meeting the request of tool life and the depth of residual stress layer.

Optimization of WEDM Process Parameters of Hybrid Composites (A413 / B4C / Fly Ash) Using Grey Relational Analysis

2014 ◽  
Vol 592-594 ◽  
pp. 658-662 ◽  
Author(s):  
J. Milton Peter ◽  
J. Udaya Prakash ◽  
T.V. Moorthy
Keyword(s):  
Surface Roughness ◽  
Fly Ash ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Hybrid Composites ◽  
Removal Rate ◽  
Relational Analysis ◽  
Grey Relational

This paper presents an optimum method to find the significant parameters affecting Wire Electrical Discharge machining (WEDM) performance using Grey relational analysis. A413 Aluminium Alloy reinforced with 20 microns of Boron Carbide and 75 microns of Fly Ash, hybrid composites was fabricated using stir casting technique. Experiments have been conducted with the process parameters like pulse on time, pulse off time, wire feed, gap voltage and weight percentage reinforcement with three different levels. The influence of each parameter on the responses material removal rate and surface roughness is established using analysis of variances (ANOVA). The optimal machining-parameters setting for minimum surface roughness and maximum material removal rate was obtained by applying Grey relational analysis.

Investigation of the Spark Cycle Effect on Material Removal Rate in Wire Electrical Discharge Machining

Manufacturing ◽  
2003 ◽  
Author(s):  
Scott F. Miller ◽  
Albert J. Shih
Keyword(s):  
Process Parameters ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Short Circuit ◽  
Wire Electrical Discharge Machining ◽  
Time Duration ◽  
Edm Process

The development of new, advanced engineering materials and the needs for precise and flexible prototype and low-volume production have made wire electrical discharge machining (EDM) an important manufacturing process to meet such demand. This research investigates the effect of spark on-time duration and spark on-time ratio, two important EDM process parameters, on the material removal rate (MRR) and surface integrity of four types of advanced material: porous metal foams, metal bond diamond grinding wheels, sintered Nd-Fe-B magnets, and carbon-carbon bipolar plates. An experimental procedure was developed. During the wire EDM, five types of constraints on the MRR due to short circuit, wire breakage, machine slide speed limit, and spark on-time upper and lower limits have been identified. An envelope of feasible EDM process parameters is created and compared across different work-materials. Applications of such process envelope to select process parameters for maximum MRR and for machining of micro features are presented.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

Modeling of Material Removal Mechanism in Micro Electric Discharge Milling of Ti-6Al-4V

2014 ◽  
Vol 592-594 ◽  
pp. 516-520 ◽  
Author(s):  
Basil Kuriachen ◽  
Jose Mathew
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Milling Process ◽  
Work Piece ◽  
Machining Parameters ◽  
Removal Mechanism ◽  
Material Removal Mechanism ◽  
Electric Discharge Milling

Micro EDM milling process is accruing a lot of importance in micro fabrication of difficult to machine materials. Any complex shape can be generated with the help of the controlled cylindrical tool in the pre determined path. Due to the complex material removal mechanism on the tool and the work piece, a detailed parametric study is required. In this study, the influence of various process parameters on material removal mechanism is investigated. Experiments were planned as per Response Surface Methodology (RSM) – Box Behnken design and performed under different cutting conditions of gap voltage, capacitance, electrode rotation speed and feed rate. Analysis of variance (ANOVA) was employed to identify the level of importance of machining parameters on the material removal rate. Maximum material removal rate was obtained at Voltage (115V), Capacitance (0.4μF), Electrode rotational Speed (1000rpm), and Feed rate (18mm/min). In addition, a mathematical model is created to predict the material removal

Influence of Process Parameters on Electrochemical Micromachining of Nimonic 75 Alloy

2017 ◽  
Author(s):  
Hariharan Perianna Pillai ◽  
Shamli Chinnakulanthai Sampath ◽  
Rajkeerthi Elumalai ◽  
Shruthilaya Hariharan ◽  
Yuvaraj Natarajan
Keyword(s):  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cycle Performance ◽  
Electrochemical Micromachining ◽  
Influence Of Process Parameters ◽  
Micro Hole ◽  
Micro Tool ◽  
Nimonic 75

Electrochemical micromachining process is one among the successful micromachining technique, which uses the electrochemical energy and is recognized for machining difficult-to-cut materials. One such material is Nimonic 75 alloy, which is used to make gas turbine components. In this study, an effort has been made to machine micro-hole profiles in Nimonic 75 with a thickness of 500 μm using two different electrolytes. A combination of sodium bromide, hydrofluoric acid and ethylene glycol has been chosen as the first electrolyte, while the second is a combination of sodium chloride and sodium nitrate. Solid tungsten carbide of diameter 500 μm is used as the tool in each case. For layout of experiments, Taguchi orthogonal array was chosen with following input parameters namely voltage, micro-tool feed rate and duty cycle. Performance characteristics such as material removal rate, overcut and conicity have been assessed for each electrolyte. Experimental results have shown that the first electrolyte yields lower values of overcut (OC) and conicity, whereas the second electrolyte gives higher material removal rate (MRR). Further, the optimal combinations of process parameters have been found by implementing the TOPSIS procedure and the results were found to be in good agreement with the experimental outcomes.

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