scholarly journals Green Ceramic Machining: Determination of the Recommended Feed Rate for Y-TZP Milling

2021 ◽  
Vol 5 (9) ◽  
pp. 231
Author(s):  
Anthonin Demarbaix ◽  
Marylou Mulliez ◽  
Edouard Rivière-Lorphèvre ◽  
Laurent Spitaels ◽  
Charles Duterte ◽  
...  
Keyword(s):  
Feed Rate ◽  
Ceramic Powder ◽  
Cutting Speed ◽  
Material Behavior ◽  
Ductile Material ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Quality ◽  
Radial Depth ◽  
Ceramic Machining

Manufacturing of advanced ceramic parts exhibiting complex geometries is laborious and expensive. Traditionally, the machining is carried out on a so-called ‘green ceramic’: a compact composed of ceramic powder held with the help of a binder. This difficulty is due not only to the composition of the material, but also to the lack of methods that determine optimal machining parameters. The goal of this paper is to apply the method based on ductile material behavior to determine a feed rate working range to ensure a machining quality. Indeed, a previous study demonstrated the limits of this method in determining cutting speed. In this case, two material removal mechanisms are observed: a mechanism dominated by pulling of the material and a proper machining mechanism. This demonstrates that the specific cutting energy is a reliable indicator for machining quality assessment. In the studied case, the recommended machining parameters to ensure quality machining of Y-TZP green ceramic with a 3 mm diameter cylindrical tool are: a cutting speed of 250 m/min, a feed per tooth of 0.037 mm/tooth, an axial depth of cut of 0.7 mm, and a radial depth of cut of 3 mm.

Cutting Temperature and Cutting Forces Investigation Based on the Taguchi Design Method when High-Speed Milling of Titanium Matrix Composites with PCD Tool

2016 ◽  
Vol 836-837 ◽  
pp. 168-174 ◽  
Author(s):  
Ying Fei Ge ◽  
Hai Xiang Huan ◽  
Jiu Hua Xu
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
High Speed ◽  
Volume Fraction ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
High Speed Milling ◽  
Radial Depth

High-speed milling tests were performed on vol. (5%-8%) TiCp/TC4 composite in the speed range of 50-250 m/min using PCD tools to nvestigate the cutting temperature and the cutting forces. The results showed that radial depth of cut and cutting speed were the two significant influences that affected the cutting forces based on the Taguchi prediction. Increasing radial depth of cut and feed rate will increase the cutting force while increasing cutting speed will decrease the cutting force. Cutting force increased less than 5% when the reinforcement volume fraction in the composites increased from 0% to 8%. Radial depth of cut was the only significant influence factor on the cutting temperature. Cutting temperature increased with the increasing radial depth of cut, feed rate or cutting speed. The cutting temperature for the titanium composites was 40-90 °C higher than that for the TC4 matrix. However, the cutting temperature decreased by 4% when the reinforcement's volume fraction increased from 5% to 8%.

Effect of machining parameters on the surface finish of a metal matrix composite under dry cutting conditions

2015 ◽  
Vol 231 (6) ◽  
pp. 913-923 ◽  
Author(s):  
Brian Boswell ◽  
Mohammad Nazrul Islam ◽  
Ian J Davies ◽  
Alokesh Pramanik
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composite ◽  
Tool Life ◽  
Surface Finish ◽  
Feed Rate ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dry Cutting

The machining of aerospace materials, such as metal matrix composites, introduces an additional challenge compared with traditional machining operations because of the presence of a reinforcement phase (e.g. ceramic particles or whiskers). This reinforcement phase decreases the thermal conductivity of the workpiece, thus, increasing the tool interface temperature and, consequently, reducing the tool life. Determining the optimum machining parameters is vital to maximising tool life and producing parts with the desired quality. By measuring the surface finish, the authors investigated the influence that the three major cutting parameters (cutting speed (50–150 m/min), feed rate (0.10–0.30 mm/rev) and depth of cut (1.0–2.0 mm)) have on tool life. End milling of a boron carbide particle-reinforced aluminium alloy was conducted under dry cutting conditions. The main result showed that contrary to the expectations for traditional machined alloys, the surface finish of the metal matrix composite examined in this work generally improved with increasing feed rate. The resulting surface roughness (arithmetic average) varied between 1.15 and 5.64 μm, with the minimum surface roughness achieved with the machining conditions of a cutting speed of 100 m/min, feed rate of 0.30 mm/rev and depth of cut of 1.0 mm. Another important result was the presence of surface microcracks in all specimens examined by electron microscopy irrespective of the machining condition or surface roughness.

scholarly journals Optimization of machining parameters in face milling using multi-objective Taguchi technique

2018 ◽  
Vol 12 (2) ◽  
pp. 104-108 ◽  
Author(s):  
Yusuf Fedai ◽  
Hediye Kirli Akin
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Taguchi Technique ◽  
Average Roughness ◽  
Multi Objective ◽  
Control Factors ◽  
Average Maximum

In this research, the effect of machining parameters on the various surface roughness characteristics (arithmetic average roughness (Ra), root mean square average roughness (Rq) and average maximum height of the profile (Rz)) in the milling of AISI 4140 steel were experimentally investigated. Depth of cut, feed rate, cutting speed and the number of insert were considered as control factors; Ra, Rz and Rq were considered as response factors. Experiments were designed considering Taguchi L9 orthogonal array. Multi signal-to-noise ratio was calculated for the response variables simultaneously. Analysis of variance was conducted to detect the significance of control factors on responses. Moreover, the percent contributions of the control factors on the surface roughness were obtained to be the number of insert (71.89 %), feed (19.74 %), cutting speed (5.08%) and depth of cut (3.29 %). Minimum surface roughness values for Ra, Rz and Rq were obtained at 325 m/min cutting speed, 0.08 mm/rev feed rate, 1 number of insert and 1 mm depth of cut by using multi-objective Taguchi technique.

Experimental Study of End Milling Force on Manganese Steel

2013 ◽  
Vol 718-720 ◽  
pp. 239-243
Author(s):  
Girma Seife Abebe ◽  
Ping Liu
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Speed ◽  
Second Order ◽  
Manganese Steel ◽  
Depth Of Cut ◽  
Machining Deformation ◽  
Radial Depth ◽  
Axial Depth

Cutting force is a key factor influencing the machining deformation of weak rigidity work pieces. In order to reduce the machining deformation and improve the process precision and the surface quality, it is necessary to study the factors influencing the cutting force and build the regression model of cutting forces. This paper discusses the development of the first and second order models for predicting the cutting force produced in end-milling operation of modified manganese steel. The first and second order cutting force equations are developed using the response surface methodology (RSM) to study the effect of four input cutting parameters (cutting speed, feed rate, radial depth and axial depth of cut) on cutting force. The separate effect of individual input factors and the interaction between these factors are also investigated in this study. The received second order equation shows, based on the variance analysis, that the most influential input parameter was the feed rate followed by axial depth, and radial depth of cut. It was found that the interaction of feed with axial depth was extremely strong. In addition, the interactions of feed with radial depth; and feed rate with radial depth of cut were observed to be quite significant. The predictive models in this study are believed to produce values of the longitudinal component of the cutting force close to those readings recorded experimentally with a 95% confident interval.

Taguchi Method Based Experiments of Titanium TC11 Flank Milling Parameters

2009 ◽  
Vol 407-408 ◽  
pp. 608-611 ◽  
Author(s):  
Chang Yi Liu ◽  
Cheng Long Chu ◽  
Wen Hui Zhou ◽  
Jun Jie Yi
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Flank Milling ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Mill Machining

Taguchi design methodology is applied to experiments of flank mill machining parameters of titanium alloy TC11 (Ti6.5A13.5Mo2Zr0.35Si) in conventional and high speed regimes. This study includes three factors, cutting speed, feed rate and depth of cut, about two types of tools. Experimental runs are conducted using an orthogonal array of L9(33), with measurement of cutting force, cutting temperature and surface roughness. The analysis of result shows that the factors combination for good surface roughness, low cutting temperature and low resultant cutting force are high cutting speed, low feed rate and low depth of cut.

Prediction the Influence of Machining Parameters for CNC Turning of Aluminum Alloy Using RSM and ANN

2020 ◽  
Vol 38 (6A) ◽  
pp. 887-895
Author(s):  
Hind H. Abdulridha ◽  
Aseel J. Haleel ◽  
Ahmed A. Al-duroobi
Keyword(s):  
Response Surface Methodology ◽  
Aluminum Alloy ◽  
Prediction Model ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Rsm Model ◽  
Good Agreement

The main objective of this paper is to develop a prediction model using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) for the turning process of Aluminum alloy 6061 round rod. The turning experiments carried out based on the Central Composite Design (CCD) of Response Surface Methodology. The influence of three independent variables such as Cutting speed (150, 175 and 200 mm/ min), depth of cut (0.5, 1 and 1.5 mm) and feed rate (0.1, 0.2 and 0.3 mm/rev) on the Surface Roughness (Ra) were analyzed through analysis of variance (ANOVA). The response graphs from the Analysis of Variance (ANOVA) present that feed-rate has the strongest influence on Ra dependent on cutting speed and depth of cut. Surface response methodology developed between the machining parameters and response and confirmation experiments reveals that the good agreement with the regression models. The coefficient of determination value for RSM model is found to be high (R2 = 0.961). It indicates the goodness of fit for the model and high significance of the model. From the result, the maximum error between the experimental value and ANN model is less than the RSM model significantly. However, if the test patterns number will be increased then this error can be further minimized. The proposed RSM and ANN prediction model sufficiently predict Ra accurately. However, ANN prediction model is found to be better compared to RSM model. The artificial neutral network is applied to experimental results to find prediction results for two response parameters. The predicted results taken from ANN show a good agreement between experimental and predicted values with the mean squared error of training indices equal to (0.000) which produces flexibility to the manufacturing industries to select the best setting based on applications.

Experimental Investigation of Machining Parameters during Turning of AISI 316L Stainless Steel Using Nano Cutting Environment

2015 ◽  
Vol 787 ◽  
pp. 361-365 ◽  
Author(s):  
T. Rajmohan ◽  
S.D. Sathishkumar ◽  
K. Palanikumar
Keyword(s):  
Stainless Steel ◽  
Feed Rate ◽  
316L Stainless Steel ◽  
Cutting Speed ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Aisi 316L ◽  
Machining Processes ◽  
Aisi 316L Stainless Steel

In modern machining processes, there are continuous cost pressures and high quality expectations in the product. Hence, it is required to explore the techniques that can reduce the cost and also increase the quality of the product. In the present work, machining performance of AISI 316L SS is assessed by the performing turning operation under nano cutting environment. Experiments have been carried out by plain turning of 48mm diameter and 600mm long rod of AISI 316L stainless steel on all geared lathe at different cutting velocities and feeds under wet machining with and without Carbon nano Tubes (CNT) inclusions using carbide inserts. The effect of cutting speed, feed rate, depth of cut on tool chip interface temperature and surface roughness are analysed using Taguchi method. Furthermore, using analysis of variance method, significant contributions of process parameters have been determined. Experimental results reveal that feed rate and cutting speed are the dominant variables on responses.

Experimental Study on the Relationship between Surface Roughness and Cutting Parameters when Face Milling High Strength Steel

2010 ◽  
Vol 139-141 ◽  
pp. 782-787
Author(s):  
Yue Ding ◽  
Wei Liu ◽  
Xi Bin Wang ◽  
Li Jing Xie ◽  
Jun Han
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
High Strength Steel ◽  
Cutting Speed ◽  
High Strength ◽  
Face Milling ◽  
Depth Of Cut ◽  
Radial Depth ◽  
The Relationship ◽  
Axial Depth

In this study, surface roughness generated by face milling of 38CrSi high-strength steel is discussed. Experiments based on 24 factorial design and Box-Behnken design method are conducted to investigate the effects of milling parameters (cutting speed, axial depth of cut and radial depth of cut and feed rate) on surface roughness, and a second-order model of surface roughness is established by using surface response methodology (RSM); Significance tests of the model are carried out by the analysis of variance (ANOVA). The results show that the most important cutting parameter is feed rate, followed by radial depth of cut, cutting speed and axial depth of cut. Moreover, it is verified that the predictive model possesses highly significance by the variance examination at a level of confidence of 99%. And the relationship between surface roughness and the important interaction terms is nonlinear.

Optimisation of Machining Parameters for Milling Polyetheretherketones (PEEK) Biomaterial

2014 ◽  
Vol 699 ◽  
pp. 198-203 ◽  
Author(s):  
Raja Izamshah Raja Abdullah ◽  
Aaron Yu Long ◽  
Md Ali Mohd Amran ◽  
Mohd Shahir Kasim ◽  
Abu Bakar Mohd Hadzley ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dimensional Precision ◽  
Good Surface

Polyetheretherketones (PEEK) has been widely used as biomaterial for trauma, orthopaedic and spinal implants. Component made from Polyetheretherketones generally required additional machining process for finishing which can be a problem especially to attain a good surface roughness and dimensional precision. This research attempts to optimize the machining and processing parameters (cutting speed, feed rate and depth of cut) for effectively machining Polyetheretherketones (PEEK) implant material using carbide cutting tools. Response Surface Methodology (RSM) technique was used to assess the effects of the parameters and their relations towards the surface roughness values. Based on the analysis results, the optimal machining parameters for the minimum surface roughness values were by using cutting speed of 5754 rpm, feed rate of 0.026 mm/tooth and 5.11 mm depth of cut (DOC).

scholarly journals Analyzing the Effect of Machining Parameters Setting to the Surface Roughness during End Milling of CFRP-Aluminium Composite Laminates

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
M. Nurhaniza ◽  
M. K. A. M. Ariffin ◽  
F. Mustapha ◽  
B. T. H. T. Baharudin
Keyword(s):  
Surface Quality ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Optimal Cutting Parameters ◽  
Cnc End Milling

The quality of the machining is measured from surface finished and it is considered as the most important aspect in composite machining. An appropriate and optimum machining parameters setting is crucial during machining operation in order to enhance the surface quality. The objective of this research is to analyze the effect of machining parameters on the surface quality of CFRP-Aluminium in CNC end milling operation with PCD tool. The milling parameters evaluated are spindle speed, feed rate, and depth of cut. The L9 Taguchi orthogonal arrays, signal-to-noise (S/N) ratio, and analysis of variance (ANOVA) are employed to analyze the effect of these cutting parameters. The analysis of the results indicates that the optimal cutting parameters combination for good surface finish is high cutting speed, low feed rate, and low depth of cut.

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