Estimation of Material Removal by Profilometer Measurements in Mass Finishing

2014 ◽  
Vol 611-612 ◽  
pp. 615-622
Author(s):  
Luana Bottini ◽  
Alberto Boschetto ◽  
Francesco Veniali
Keyword(s):  
Plastic Deformation ◽  
Surface Modification ◽  
Surface Morphology ◽  
Process Parameters ◽  
Material Removal ◽  
Machining Process ◽  
Local Surface ◽  
Mass Finishing ◽  
Barrel Finishing ◽  
The Relationship

This paper presents a new procedure to estimate the material removal (MR) in such conditions or operations where small amount of material or wear occur. The monitoring of material removal is essential to understand the machining mechanisms of several processes such as super finishing ones. For example the study of some mass finishing (MF) operations, i. e. the barrel finishing (BF) and the spindle finishing (SF), have been always limited by the difficulty to measure the local surface modification. Thus there is no knowledge about the relationship between process parameters and obtainable surface quality. The procedure is based on profilometer measurements typically used to characterized local surface morphology. An algorithm automatically finds the most representative peak of the profile. The comparison between the Abbot-Firestone curves, related to peaks achieved in different condition, permits to measure the volume of material removed by the operation. This method overcomes the well-known problem to repositioning the instrument in the same place when the part is moved from machining process to measurement one. In the case of BF, experimental demonstrated the reliability of this methodology to provide the evolution of material removed as a function of working time. Moreover the graphical plot of the representative peak at different times gave important information about machining mechanism. In particular it allowed to verify assumptions regarding the plastic deformation and the peak cutting which takes place.

scholarly journals Modelling of Rotary EDM Process Parameters of Inconel 718 Using Artificial Neural Networks

Mechanika ◽  
2020 ◽  
Vol 26 (6) ◽  
pp. 540-544
Author(s):  
Jayaraj JEEVAMALAR ◽  
Sundaresan RAMABALAN ◽  
Chinnamuthu SENTHILKUMAR
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Process Parameters ◽  
Inconel 718 ◽  
Machining Process ◽  
Artificial Neural ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Matlab Programming ◽  
The Relationship

Modelling is used for correlating the relationship between the input process parameters and the output responses during the machining process. To characterize real-world systems of considerable complexity, an Artificial Neural Network (ANN) model is regularly used to replace the mathematical approximation of the relationship. This paper explains the methodological procedure and the outcome of the ANN modeling process for Electrical Discharge Drilling of Inconel 718 superalloy and hollow tubular copper as tool electrode. The most important process parameters in this work are peak current, pulse on time and pulse off time with machining performances of material removal rate and surface roughness. The experiments were performed by L20 Orthogonal Array. In such conditions, an Artificial Neural Network model is developed using MATLAB programming on the Feed Forward Back Propagation technique was used to predict the responses. The experimental data were separated into three parts to train, test the network and validate the model. The developed model has been confirmed experimentally for training and testing in considering the number of iterations and mean square error convergence criteria. The developed model results are to approximate the responses fairly exactly. The model has the mean correlation coefficient of 0.96558. Results revealed that the proposed model can be used for the prediction of the complex EDM drilling process.

Optimization of Process Parameters on Ti-6Al-4V Using Central Composite Design Method

2011 ◽  
Vol 189-193 ◽  
pp. 1393-1400 ◽  
Author(s):  
M.M. Rahman
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Peak Current ◽  
Long Pulse ◽  
Pulse On Time

Electrical discharge machining (EDM) is relatively modern machining process having distinct advantages over other machining processes and able to machine Ti-alloys effectively. This paper attempts to investigate the effects of process parameters on output response of titanium alloy Ti-6Al-4V in EDM utilizing copper tungsten as an electrode and positive polarity of the electrode. Mathematical models for material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR) are developed in this paper. Design of experiments method and response surface methodology techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance. It can be seen that as the peak current increases the TWR decreases till certain ampere and then increases. The excellent surface finish is investigated in this study at short pulse on time and in contrast the long pulse duration causes the lowest EWR. Long pulse off time provides minimum EWR and the impact of pulse interval on EWR depends on peak current. The result leads to wear rate of electrode and economical industrial machining by optimizing the input parameters. It found that the peak current, servo voltage and pulse on time are significant in material removal rate and surface roughness. Peak current has the greater impact on surface roughness and material removal rate.

scholarly journals Multi-Objective Process Parameter Optimization for Surface Roughness and Material Removal Rate in Face Milling of Al 6061 T6 Alloy

2019 ◽  
Vol 9 (2) ◽  
pp. 137-142
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Face Milling ◽  
Machining Process ◽  
Depth Of Cut ◽  
Al 6061

This study uses Taguchi methodology and Gray Relational Analysis approach to explore the optimization of face milling process parameters for Al 6061 T6 alloy.Surface Roughness (Ra), Material Removal Rate (MRR) has been identified as the objective of performance and productivity.The tests were performed by selecting cutting speed (mm / min), feed rate (mm / rev) and cutting depth (mm) at three settings on the basis of Taguchi's L9 orthogonal series.The grey relational approach was being used to establish a multiobjective relationship between both the parameters of machining and the characteristics of results. To find the optimum values of parameters in the milling operation, the response list and plots are used and found to be Vc2-f1-d3. To order to justify the optimum results, the confirmation tests are performed.The machining process parameters for milling were thus optimized in this research to achieve the combined goals such as low surface roughness and high material removal rate on Aluminum 6061 t6.It was concluded that depth of cut is the most influencing parameter followed by feed rate and cutting velocity.

Optimization of EDM Process Parameters of Thixoformed A356-5TiB2 In Situ Composites

2020 ◽  
Vol 978 ◽  
pp. 271-276
Author(s):  
Sahini Deepak Kumar ◽  
Shailesh Dewangan ◽  
Joyjeet Ghose ◽  
S.K. Jha
Keyword(s):  
Surface Morphology ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Surface Integrity ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
In Situ Composites ◽  
Edm Process

The present work reports the influence of various Electric-Discharge Machining (EDM) process parameters on the surface morphology and EDM characteristics of thixoformed A356-5TiB2 in-situ composites. The important EDM parameters such as pulse current, pulse-on time, Duty Cycle, etc. on Surface morphology and Material removal rate of the thixoformed A356-5TiB2 in-situ composites have been investigated. Further, the machining parameters were optimized using Fuzzy-logic and grey relational analysis approach. The effect of EDM parameters and their interactions on the erosion behavior of A356-5TiB2 in-situ composites on various aspects of surface integrity and Material Removal rate (MRR) is reported. The surface integrity during EDM was characterized by Scanning Electron Microscope and analyzed from the machinability point of view. Thus, this work is an attempt to study the machinability behavior of thixoformed A356-5TiB2 in-situ composites.

Effects of Process Parameters on Material Removal Rate and Surface Roughness in Wedm of H-13 Die Tool Steel

2018 ◽  
Vol 28 ◽  
pp. 55-66 ◽  
Author(s):  
Kuldeep Singh ◽  
Khushdeep Goyal ◽  
Deepak Kumar Goyal
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Pulse On Time ◽  
Pulse Off Time

In research work variation of cutting performance with pulse on time, pulse off time, wire type, and peak current were experimentally investigated in wire electric discharge machining (WEDM) process. Soft brass wire and zinc coated diffused wire with 0.25 mm diameter and Die tool steel H-13 with 155 mm× 70 mm×14 mm dimensions were used as tool and work materials in the experiments. Surface roughness and material removal rate (MRR) were considered as performance output in this study. Taguchi method was used for designing the experiments and optimal combination of WEDM parameters for proper machining of Die tool steel (H-13) to achieve better surface finish and material removal rate. In addition the most significant cutting parameter is determined by using analysis of variance (ANOVA). Keywords Machining, Process Parameters, Material removal rate, Surface roughness, Taguchi method

Metal Machinability Evaluation with DEA Method

2006 ◽  
Vol 532-533 ◽  
pp. 548-551
Author(s):  
Yao Chen ◽  
Ai Bing Yu ◽  
Da Wei Jia ◽  
Nan Zhao
Keyword(s):  
Process Parameters ◽  
Evaluation System ◽  
Programming Model ◽  
Machining Process ◽  
Data Envelopment ◽  
Output Data ◽  
Optimal Values ◽  
Metal Materials ◽  
Dea Method ◽  
The Relationship

Data envelopment analysis (DEA) evaluation system of metal materials was established. Evaluated metal materials were regarded as decision making units (DMUs). Property parameters of metal materials were selected as inputs of DMUs, and machining process parameters were selected as outputs of DMUs. Input and output data sequences could be obtained through data processing operations. Mathematics programming model was founded and optimal values of all the evaluated materials were calculated based on the model. Machinabilities of metal materials could be evaluated by comparing the optimal values. Taken 1Cr18Ni9Ti, GCr15, Q235, 45# and LY11 for example, machinabilities of five metal materials were ranked. Research results suggest that DEA method can synthetically consider the relationship between property parameters and machining process parameters. DEA is proved to be a reasonable and available method to evaluate metal material machinability.

Research on Green Technology System of Oriented LCA Electromechanical Products

2013 ◽  
Vol 312 ◽  
pp. 909-913
Author(s):  
Cheng You Yuan ◽  
Yu Xia Yang ◽  
Liu Liang Chen
Keyword(s):  
Process Parameters ◽  
Information Integration ◽  
Green Technology ◽  
Machining Process ◽  
System Structure ◽  
Technology System ◽  
Depth Analysis ◽  
Electromechanical Products ◽  
Electromechanical Product ◽  
The Relationship

In view of the current LCA software, electromechanical products green design and green technology system are lacks of good support issues. From the electromechanical product manufacturing, processs technology characteristics, process parameters and green characteristic starting, to establish the overall technology system flow, system structure and system function model, and then from the view of electromechanical product life cycle green information integration, to analyze product BOM structure and green information integration strategy. According to the relationship between machining process parameters and process output indicators factors, to set up electromechanical products process parameter model and the quantification method under LCA, using GBP algorithm selects optimization program, to achieve green manufacturing process. From the point of integration in-depth analysis, the analysis of the relationship between system functions and multiple targets of process parameters, and further development of a prototype system.

Polishing of Ultra Smooth Surface with Nanoparticle Colloid Jet

2009 ◽  
Vol 404 ◽  
pp. 143-148 ◽  
Author(s):  
Fei Hu Zhang ◽  
Xiao Zong Song ◽  
Yong Zhang ◽  
Dian Rong Luan
Keyword(s):  
Process Parameters ◽  
Material Removal ◽  
Smooth Surface ◽  
Removal Rate ◽  
Machining Process ◽  
Theoretical Dependence ◽  
Force Microscopy ◽  
Machining System ◽  
Glass Surfaces ◽  
Nanoparticle Colloid

A nanoparticle colloid jet machining system has been developed for polishing ultra smooth surface of brittle materials. Interaction between nanoparticles and work surface in nanoparticle colloid jet machining has been given, and the theoretical dependence of the material removal rate with various important process parameters of the nanoparticle colloid jet machining have been investigated through material removal experiments. Some material removal results of nanoparticle colloid jet machining show that it is possible to obtain removal rates of one nanometer level per minute for glass surfaces with appropriate machining process parameters. A K9 glass surface was polished for obtaining ultra smooth surface. The surface roughness value of atomic force microscopy (AFM) observations is under 1nm Rms.

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