A novel ensemble method based on SBLMD-ANN-MOPSO approach for predicting the milling stability regimes

2022 ◽  
Author(s):  
Rohit Mishra ◽  
Bhagat Singh
Keyword(s):  
Prediction Models ◽  
Metal Removal ◽  
Removal Rate ◽  
Training Algorithms ◽  
Metal Removal Rate ◽  
Activation Functions ◽  
Data Set ◽  
Milling Operations ◽  
Marquardt Algorithm ◽  
Excited Vibration

Abstract In recent decades, lots of work has been done to mitigate self excited vibration effects in milling operations. Still, a robust methodology is yet to be developed that can suggest stability bounds pertaining to higher metal removal rate (MRR). In the present work, experimentally acquired acoustic signals in milling operation have been computed using a modified Local Mean Decomposition (SBLMD) technique in order to cite tool chatter features. Further, three artificial neural network (ANN) training algorithms viz. Resilient Propagation (RP), Conjugate Gradient-Based (CGP) and Levenberg-Marquardt Algorithm (LM) and two activation functions viz. Hyperbolic Tangent Sigmoid (TANSIG) and Log Sigmoid (LOGSIG) has been used to train the acquired chatter vibration and metal removal rate data set. Over-fitting or under-fitting issues may arise from the random selection of a number of hidden neurons. The solution to these problems is also proposed in this paper. Among these training algorithms and activation functions, a suitable one has been selected and further invoked to develop prediction models of chatter severity and metal removal rate. Finally, Multi-Objective Particle Swarm Optimization (MOPSO) has been invoked to optimize developed prediction models for obtaining the most favourable range of input parameters pertaining to stable milling with higher productivity.

Ensembled local mean decomposition and genetic algorithm approach to investigate tool chatter features at higher metal removal rate

2020 ◽  
pp. 107754632097115
Author(s):  
Pankaj Gupta ◽  
Bhagat Singh
Keyword(s):  
Genetic Algorithm ◽  
Prediction Models ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Metal Removal Rate ◽  
Local Mean Decomposition ◽  
Local Mean ◽  
Chatter Index ◽  
Selection Of

Improper selection of cutting parameters leads to regenerative chatter and loss in productivity. In the present work, a methodology has been proposed to select a proper combination of input cutting parameters for stable turning with improved metal removal rate. Chatter signals generated during the turning of Al6061-T6 have been acquired using a microphone. Stability lobes diagram has been plotted to access the stability regime. Further, to study the effect of feed rate on stability, the recorded signals have been processed using local mean decomposition signal processing technique, followed by the selection of dominating product functions using Fourier transform. The decomposed signals have been used to evaluate the new output parameter, that is, chatter index. Prediction models of chatter index and metal removal rate have been developed. Moreover, these prediction models have been optimized using multi-objective genetic algorithm for ascertaining the optimal range of cutting parameters for stable turning with higher metal removal rate. Finally, obtained stable range has been validated by performing more experiments.

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

2018 ◽  
Vol 49 (2) ◽  
pp. 62-81 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Removal ◽  
Removal Rate ◽  
Statistical Significance ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Chatter Index ◽  
Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Rajesh Kumar Bhushan
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Nose Radius ◽  
Multiresponse Optimization

Optimization in turning means determination of the optimal set of the machining parameters to satisfy the objectives within the operational constraints. These objectives may be the minimum tool wear, the maximum metal removal rate (MRR), or any weighted combination of both. The main machining parameters which are considered as variables of the optimization are the cutting speed, feed rate, depth of cut, and nose radius. The optimum set of these four input parameters is determined for a particular job-tool combination of 7075Al alloy-15 wt. % SiC (20–40 μm) composite and tungsten carbide tool during a single-pass turning which minimizes the tool wear and maximizes the metal removal rate. The regression models, developed for the minimum tool wear and the maximum MRR were used for finding the multiresponse optimization solutions. To obtain a trade-off between the tool wear and MRR the, a method for simultaneous optimization of the multiple responses based on an overall desirability function was used. The research deals with the optimization of multiple surface roughness parameters along with MRR in search of an optimal parametric combination (favorable process environment) capable of producing desired surface quality of the turned product in a relatively lesser time (enhancement in productivity). The multi-objective optimization resulted in a cutting speed of 210 m/min, a feed of 0.16 mm/rev, a depth of cut of 0.42 mm, and a nose radius of 0.40 mm. These machining conditions are expected to respond with the minimum tool wear and maximum the MRR, which correspond to a satisfactory overall desirability.

Optimization of MRR and Surface Roughness of AlMg3 (AA5754) Alloy in CNC Lathe Machine by Using Taguchi Method

2018 ◽  
Vol 877 ◽  
pp. 110-117 ◽  
Author(s):  
Poornesh Kumar Chaturvedi ◽  
Harendra Kumar Narang ◽  
Atul Kumar Sahu
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Metal Removal ◽  
Removal Rate ◽  
Surface Condition ◽  
Point Of View ◽  
Depth Of Cut ◽  
Metal Removal Rate ◽  
Cnc Lathe ◽  
Lathe Machine

Quality of the product is the major concern in manufacturing industries from customers as well as producers point of view. There are number of factors in the product such as surface condition, height, weight, length, width etc., which may be consider for the measurement of the quality. Surface roughness and Metal Removal Rate (MRR) are the two main outcomes on which numerous researchers have applied different approaches for several years to get optimum results. In this study, Taguchi Method is applied for getting optimum parameters settings for Surface roughness and Metal Removal Rate (MRR) in case of turning AlMg3 (AA5754) in CNC Lathe machine, which is an aluminum alloy having diameter 20 mm and length 100 mm. The three parameters i.e. spindle speed, feed rate and depth of cut with 3 levels are taken as the process variables and the working ranges of these parameters for conducting experiments are selected based on Taguchi’s L9 Orthogonal Array (OA) design. To analyze the significant process parameters; main effect plots for data means and for S/N ratio are generated using Minitab statistical software.

Effect of the Al2O3 powder addition on the metal removal rate and the surface roughness of the electrochemical grinding machining

2020 ◽  
Vol 234 (12) ◽  
pp. 1538-1548 ◽  
Author(s):  
Hossam M Yehia ◽  
Mohamed Hakim ◽  
Ahmed El-Assal
Keyword(s):  
Surface Roughness ◽  
Metal Removal ◽  
Removal Rate ◽  
Lower Surface ◽  
Maximum Effect ◽  
Metal Removal Rate ◽  
Powder Addition ◽  
Different Depths ◽  
Electrochemical Grinding ◽  
Better Than

The integrated electrochemical grinding machining has received wide acceptance in the aircraft turbine industry for the machining of blades, vanes, and honeycomb seal rings. Also, medical devices, instruments and forceps, shells, precision nozzles, instrument coupling, and air rotor motors that produced from stainless steel and new materials have all successfully been accomplished with electrochemical grinding. To improve the metal removal rate and to reduce the surface roughness ( Ra) of the electrochemical grinding at high voltages, an integration between the alumina abrasive jet and the electrochemical grinding machining has been performed. The effect of the Al2O3 abrasive content on the metal removal rate and the Ra of the K110 alloy steel using Everite electrochemical grinding 618 at different voltages, different feed rates, different electrolyte NaCl concentrations, and different depths of the cut were successfully investigated. The results revealed that the abrasive electrochemical grinding was better than the electrochemical grinding results. The maximum effect of the Al2O3 on the metal removal rate was achieved at 5 wt.%. The current density in the machining gap was affected by the addition of the Al2O3, where it was decreased at percentages over 5-wt.% Al2O3. The abrasive electrochemical grinding resulted in lower surface roughness than the electrochemical grinding process.

scholarly journals An Efficient Third-Order Full-Discretization Method for Prediction of Regenerative Chatter Stability in Milling

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Chao Huang ◽  
Wen-An Yang ◽  
Xulin Cai ◽  
Weichao Liu ◽  
YouPeng You
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Discretization Method ◽  
Chatter Stability ◽  
Computationally Efficient ◽  
Third Order ◽  
Regenerative Chatter ◽  
Full Discretization ◽  
Milling Operations ◽  
Comparison Results

The prediction of regenerative chatter stability has long been recognized as an important issue of concern in the field of machining community because it limits metal removal rate below the machine’s capacity and hence reduces the productivity of the machine. Various full-discretization methods have been designed for predicting regenerative chatter stability. The main problem of such methods is that they can predict the regenerative chatter stability but do not efficiently determine stability lobe diagrams (SLDs). Using third-order Newton interpolation and third-order Hermite interpolation techniques, this study proposes a straightforward and effective third-order full-discretization method (called NI-HI-3rdFDM) to predict the regenerative chatter stability in milling operations. Experimental results using simulation show that the proposed NI-HI-3rdFDM can not only efficiently predict the regenerative chatter stability but also accurately identify the SLD. The comparison results also indicate that the proposed NI-HI-3rdFDM is very much more accurate than that of other existing methods for predicting the regenerative chatter stability in milling operations. A demonstrative experimental verification is provided to illustrate the usage of the proposed NI-HI-3rdFDM to regenerative chatter stability prediction. The feature of accurate computing makes the proposed NI-HI-3rdFDM more adaptable to a dynamic milling scenario, in which a computationally efficient and accurate chatter stability method is required.

EXPERIMENTAL INVESTIGATIONS INTO THE INFLUENCING PARAMETERS OF ELECTROCHEMICAL MACHINING OF AISI 202

2008 ◽  
Vol 07 (02) ◽  
pp. 337-343 ◽  
Author(s):  
T. SEKAR ◽  
R. MARAPPAN
Keyword(s):  
Surface Roughness ◽  
Metal Removal ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
High Energy ◽  
Experimental Investigations ◽  
Metal Removal Rate ◽  
Hard Materials ◽  
Influencing Parameters ◽  
Traditional Process

Electrochemical machining (ECM) is a non-traditional process used mainly to cut hard or difficult to cut metals, where the application of a more traditional process is not convenient. Those difficult to cut metals demand high energy to form chips, which can result in thermal effects due to the high temperatures inherent to the process in the chip–tool interface. In traditional processes, the heat generated during the cut is dissipated to the tool, chip, workpiece and environment, affecting the surface integrity of the workpiece, mainly for those hard materials. In this work, experimental investigations have been made on the various influencing parameters involved in the Metal removal rate (MRR) and Surface roughness using ECM on AISI 202 steel. The major intervening parameters are studied and the relationship between the parameters has been determined to achieve maximum metal removal rate and minimum surface roughness by using NaNO 3-Aqua solution.

Factors Influencing the Performance of Grinding Wheels

1959 ◽  
Vol 81 (3) ◽  
pp. 187-199 ◽  
Author(s):  
E. J. Krabacher
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Grinding Wheel ◽  
Metal Removal Rate ◽  
Grinding Wheels ◽  
Wheel Wear ◽  
Grinding Wheel Wear ◽  
Grinding Ratio ◽  
Material Hardness ◽  
Chip Load

Optimum utilization of grinding wheels can best be achieved if the nature of their performance and wear characteristics, and the factors that affect these characteristics, are understood and applied. As reported in this paper, a comprehensive, continuing, grinding-research program has contributed to such an understanding. A study of the nature of grinding-wheel wear indicates that the grinding-wheel wear curve is similar to those of other cutting tools. It demonstrates further that the type of grinding operation significantly affects the nature of wheel wear. A unique technique has been developed for very accurately measuring grinding-wheel wear. This measured wear may be translated into terms of “grinding ratio,” which is the generally accepted parameter for measuring wheel wear. It is the ratio of the volume of metal removed per unit volume of wheel worn away. Extensive studies have been carried out to determine the effect of mechanical variables on grinding ratio, power required in metal removal, and on surface finish. Experimental findings indicate that grinding ratio decreases with increased metal-removal rate and increases with workpiece diameter, decreased chip load, and increased concentration of grinding fluid. Power is found to increase with both the metal-removal rate and the amount of metal removed. It increases slightly with workpiece diameter and is affected little by work-material hardness. Surface finish is found to improve with decreased metal-removal rate and decreased chip load. It also is affected little by work diameter or work-material hardness. Fundamental research in the mechanics of wheel wear is supplying much additional information in the study of grinding-wheel wear. The measurement of grinding forces employing a cylindrical grinding dynamometer provides the opportunity for relating the wear of grinding wheels to the basic mechanics of the process through such fundamental quantities as grinding forces, specific energy, and grinding friction. Two additional experimental techniques for the study of chip formation in grinding have also proved to be most useful research tools. A “quick-stop” apparatus is used to freeze the grinding action by accelerating a tiny workpiece almost instantaneously to grinding-wheel speed. Another technique permits the comparison of the shape of the grinding grit and that of the contour of its path through the workpiece by a unique replicating method.

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