scholarly journals Chatter Stability Prediction and Process Parameters’ Optimization of Milling Considering Uncertain Tool Information

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1071
Author(s):  
Lijun Lin ◽  
Mingge He ◽  
Qingyuan Wang ◽  
Congying Deng
Keyword(s):  
Machine Tool ◽  
Process Parameters ◽  
Optimization Model ◽  
Removal Rate ◽  
Parameters Optimization ◽  
Generalized Regression Neural Network ◽  
Machining Parameters ◽  
Milling Stability ◽  
Machine Tool Dynamics ◽  
Tool Dynamics

Stability is the prerequisite of a milling operation, and it seriously depends on machining parameters and machine tool dynamics. Considering that the tool information, including the tool clamping length, feeding direction, and spatial position, has significant effects on machine tool dynamics, this paper presents an efficient method to predict the tool information dependent-milling stability. A generalized regression neural network (GRNN) is established to predict the limiting axial cutting depth, where the machining parameters and tool information are taken as input variables. Moreover, an optimization model is proposed based on the machining parameters and tool information to maximize the material removal rate (MRR), where the GRNN model is taken as the stability constraint. A particle swarm optimization (PSO) algorithm is introduced to solve the optimization model and provide an optimal configuration of the machining parameters and tool information. A case study has been developed to train a GRNN model and establish an optimization model of a real machine tool. Then, effects of the tool information on milling stability were discussed, and an origin-symmetric phenomenon was observed as the feeding direction varied. The accuracy of the solved optimal process parameters corresponding to the maximum MRR was validated through a milling test.

Investigating the Effect of Machining Parameters on Microdrilling of Titanium Grade 19 Alloy

2013 ◽  
Author(s):  
Shivraj Yeole ◽  
Nagabhushana Ramesh Nunna ◽  
Balu Naik Banoth
Keyword(s):  
Process Parameters ◽  
Material Removal ◽  
Removal Rate ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Micro Edm ◽  
Electrode Diameter ◽  
Micro Holes ◽  
Titanium Grade ◽  
Edm Process

Electrical Discharge Micro Drilling (EDMD) is considered as one of the most effective method for machining difficult to cut and hard materials like titanium alloy. However, selection of process parameters for achieving superior surface finish, higher machining rate and accuracy is a challenging task in drilling micro-holes. In this paper, an attempt is made to optimize micro-EDM process parameters for drilling micro holes on titanium grade 19 alloy. In order to verify the optimal micro-EDM process parameters settings, material removal rate (MRR), electrode wear rate (EWR) and over cut (OC) were chosen as the responses to be observed. Pulse on time, pulse off time, electrode diameter and current were selected as the governing process parameters for evaluation by Taguchi method. Nine micro holes of 300 μm, 400 μm and 500 μm were drilled using L9 orthogonal array (OA) design. Optimal combination of machining parameters were obtained through Signal-to-Noise (S/N) ratio analysis. It is seen that machining performances like material removal rate and overcut are affected by the peak current whereas electrode wear is affected by peak current and electrode diameter. Morphology of the micro holes has been studied through SEM micrographs of machined micro-hole.

Study on Ultrasonic Vibration in Gas and Optimization of a Novel Process of EDM

2013 ◽  
Vol 675 ◽  
pp. 365-369 ◽  
Author(s):  
Yan Cherng Lin ◽  
Han Ming Chow ◽  
Hai Ping Tsui ◽  
Yuan Feng Chen
Keyword(s):  
Ultrasonic Vibration ◽  
Process Parameters ◽  
High Efficiency ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Main Process ◽  
Machining Parameters ◽  
Machining Performance ◽  
Dielectric Fluids ◽  
Edm Process

The aim of this study is to investigate the machining characteristics of ultrasonic vibration assisted electrical discharge machining (EDM) process using gas media as the dielectric fluids. The process parameters were designed based on Taguchi method to conduct the experimental works. The main process parameters such as machining polarity, peak current, pulse duration, air pressure, working time, and servo reference voltage were chosen to determine their effects on machining performance in terms of material removal rate and surface roughness for SKD 61 tool steels. The experimental response values were transferred to signal-to-noise (S/N) ratios, and then the significant machining parameters associated with the machining performance were examined by analysis of variance (ANOVA). Therefore, the technique of ultrasonic vibration assisted EDM process in gas media was established with the concerning features related to environmentally friendly, high efficiency, and high machining quality to fit the demands of modern manufacturing applications.

Optimization of WEDM Process Parameters

2014 ◽  
Vol 592-594 ◽  
pp. 831-835 ◽  
Author(s):  
Vikram Singh ◽  
Sharad Kumar Pradhan
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The objective of the present work is to investigate the effects of various WEDM process parameters like pulse on time, pulse off time, corner servo, flushing pressure, wire feed rate, wire tension, spark gap voltage and servo feed on the material removal rate (MRR) & Surface Roughness (SR) and to obtain the optimal settings of machining parameters at which the material removal rate (MRR) is maximum and the Surface Roughness (SR) is minimum in a range. In the present investigation, Inconel 825 specimen is machined by using brass wire as electrode and the response surface methodology (RSM) is for modeling a second-order response surface to estimate the optimum machining condition to produce the best possible response within the experimental constraints.

scholarly journals Optimizing Process Parameters of Spark and Wire-Cut Edm through Anova using Stainless Steel Aisi 316 Material

2019 ◽  
Vol 9 (2) ◽  
pp. 817-821
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Process Parameters ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Steel Aisi ◽  
Aisi 316 ◽  
Pulse On Time ◽  
Stainless Steel Aisi

In the present research work, Stainless Steel AISI 316 as per ASTM A 276 has been employed as the base material to perform Spark and Wire-Cut EDM. The main agenda behind performing Spark and Wire-Cut EDM on Stainless Steel AISI 316 is to find out the effect of machining parameters like surface roughness (SR) and MRR (Material Removal Rate). In-case of wire-cut EDM, brass wire) of 0.25 mm diameter is used as a tool and distilled water is used as dielectric fluid and experimental process parameters like Current (A) (2, 3 and 4 Amps), Pulse ON time (B) (25, 30 and 35 μs) and Wire feed rate (C) (40, 60 and 80 mm/sec). Similarly for spark cut EDM copper rod of 12 mm diameter and 65 mm length. Process parameters like Current (A) (6, 12 and 16 Amps), Voltage (B) (30, 35 and 40 Volts) and Pulse ON time (C) (50, 100 and 200μs) were maintained during the experimentation. Statistical tools ANOVA & L-9 Orthogonal Array (OA) have been employed to optimize the machining parameters like Surface Roughness (SR) and MRR (Material Removal Rate).

scholarly journals Multi-Performance Optimization in Electrical Discharge Machining of Al2O3 Ceramics Using Taguchi Base AHP Weighted TOPSIS Method

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1647
Author(s):  
Yue-Peng Zeng ◽  
Chiang-Lung Lin ◽  
Hong-Mei Dai ◽  
Yan-Cherng Lin ◽  
Jung-Chou Hung
Keyword(s):  
Process Parameters ◽  
Performance Optimization ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Statistical Technique ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Relative Closeness ◽  
Machining Parameter

The main application of electrical discharge machining in ceramic processing is limited to conductive ceramics. However, the most commonly used non-conductive potteries in modern industry, such as aluminum oxide (Al2O3), also reveal the limitations of choosing a suitable process. In this study, Taguchi based TOPSIS coupled with AHP weight method to optimize the machining parameters of EDM on Al2O3 leads to better multi-performance. The results showed that the technique is suitable for tackling multi-performance machining parameter optimization. The adhesive foil had a significant impact on material removal rate, electrode wear rate, and surface roughness, according to the findings. In addition, the response graph of relative closeness is used to determine the optimal combination levels of machining parameters. A confirmation test revealed a good agreement between predicted and experimental preference values at an optimum combination of the input parameters. The suggested experimental and statistical technique is a simple, practical, and reliable methodology for optimizing EDM process parameters on Al2O3 ceramics. This approach might be utilized to optimize and improve additional process parameters in the future.

scholarly journals Optimization of CNC Turning Parameters in Machining EN19 using Face Centered Central Composite Design Based RSM

2020 ◽  
Vol 9 (2) ◽  
pp. 889-896
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Removal Rate ◽  
Cutting Speed ◽  
Vital Role ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Software Analysis ◽  
Central Composite

Manufacturing a defect free (quality) product is playing a vital role in today’s globally competitive, customer oriented era. Meeting the demand of the market by producing sufficient quantity is another challenge. Achieving greater production rates without compromising on quality, increases the complexity of the task. Adopting modern manufacturing methods like CNC turning are essential to meet the above requirements. EN19 is an important member in the family of alloy steels, which has a wide variety of applications in automobile and machine tool industries. Optimization of machining parameters is crucial in obtaining the required outputs such as quality and productivity. In this work, optimization of CNC turning parameters for machining EN19 alloy steel is performed. The number of experiments was designed using face centred central composite based response surface methodology with varied independent process parameters namely cutting speed, feed and depth of cut. After designing the experiments, the performance measures such as surface roughness of the test samples and Material Removal Rate (MRR) is calculated using the existing formulae. The influence of parameters on MRR and surface roughness are determined by analysis of variance (ANOVA) and for significance interactions of the process parameters are also considered. Using MINITAB 17 software analysis is performed. Further, regression analysis has been done and second order mathematical model is obtained. Using desirability approach, optimization is carried out.

Sign in / Sign up

Export Citation Format

Share Document