Prediction and optimization of surface roughness in milling of medium density fiberboard (MDF) based on Taguchi orthogonal array experiments

Holzforschung ◽  
2008 ◽  
Vol 62 (2) ◽  
pp. 209-214 ◽  
Author(s):  
Vinayak N. Gaitonde ◽  
S. Ramesh Karnik ◽  
João Paulo Davim
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Orthogonal Array ◽  
Medium Density Fiberboard ◽  
Cutting Speed ◽  
Medium Density ◽  
Taguchi Optimization ◽  
Taguchi Orthogonal Array ◽  
Roughness Model ◽  
Order Surface

Abstract The main objective of this paper was to develop a mathematical model to predict the surface roughness and to determine the optimal cutting conditions during milling of medium density fiberboard. The milling experiments were carried out as per Taguchi orthogonal array with feed rate and cutting speed as the controlling parameters. A second-order surface roughness model has been developed using the methodology of response surface analysis. The paper presents the details of analysis of variance to validate the developed model. The Taguchi optimization results show that the surface roughness can be optimized with lower feed rate and higher cutting speed values.

scholarly journals Noncontact Surface Roughness Evaluation of Milling Surface Using CNN-Deep Learning Models

2021 ◽  
Author(s):  
Binayak Bhandari ◽  
Gijun Park
Keyword(s):  
Surface Roughness ◽  
Quality Control ◽  
Deep Learning ◽  
Orthogonal Array ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Test Accuracy ◽  
Machined Surface ◽  
Practical Applications ◽  
Taguchi Orthogonal Array

Abstract This paper presents the analysis of end milled machined surfaces backed with experimental and deep learning model investigations. The effect of process parameters like spindle speed, feed rate, depth of cut, cutting speed, and machining duration were investigated to find machined surface roughness using Taguchi orthogonal array. The experiments were conducted on Aluminum A3003, a common material widely used in industries. Following standard DOE using Taguchi orthogonal array, surface roughness was recorded for each machining experiment. Surface roughnesses for the current study were categorized into four classes viz., fine, smooth, rough, and coarse based on the roughness value Ra. Images of the machined surface were used to develop CNN models for surface roughness class prediction. The prediction accuracies of the CNN models were compared for five types of optimizers. It was found that RAdam optimizer performed better among others with the training and test accuracy of 96.30% and 92.91% respectively. The accuracy of the prediction is higher than 90% thus has the potential to substitute human quality control procedures, saving time, energy, and cost. Conversely, the developed CNN model can assist in acquiring preferred machining conditions in advance. Finally, it can eliminate the dependency on expensive surface roughness measuring devices and have enormous practical applications in quality control processes.

OPTIMIZATION OF CYLINDRICAL GRINDING PROCESS PARAMETERS OF SS316L AUSTENTIC STAINLESS STEEL BY TAGUCHI METHOD

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Sankar Ganesh S ◽  
Thirumal P ◽  
Anbarasu M
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Orthogonal Array ◽  
Cutting Speed ◽  
Optimal Solution ◽  
Depth Of Cut ◽  
Cylindrical Grinding ◽  
Minimum Surface ◽  
Grinding Parameters ◽  
Grinding Machine

The main objective of this study is to optimize the cylindrical grinding parameters that can be utilized to predict optimal grinding parameters to achieve minimum surface roughness of a material. A SS 317L Austentic steel round rod of 80 mm x 168 mm was considered for cylindrical grinding in this study. Cutting speed, depth of cut and feed rate were chosen as input variables while Surface roughness (Ra) selected as output response. An L9 orthogonal array was selected for this study and S/N ratios were analyzed to study the surface roughness characteristics. Nine experiments were conducted in the surface grinding machine with different values of input parameters obtained from the orthogonal array. The surface roughness values were optimized in the optimization software (Minitab version 17) and the optimal solution was obtained for minimum response. Minimum surface roughness is achieved with 100 rpm cutting speed, 0.03 mm depth of cut and 1 mm/s feed rate. The confirmation experiments were conducted for the optimal solution obtained from Taguchi experiment and the results are verified.

Surface Roughness Model when Machining Aluminum Nitride Ceramic with Two Flute Square End Micro Grain Solid Carbide End Mill

2013 ◽  
Vol 747 ◽  
pp. 282-286 ◽  
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
K.A. Abou-El-Hossein ◽  
D. Sujan
Keyword(s):  
Surface Roughness ◽  
Aluminum Nitride ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
End Mill ◽  
Roughness Model ◽  
Solid Carbide

This research presents the performance of Aluminum Nitride ceramic in end milling using two flute square end micro grain solid carbide end mill under dry cutting. Surface finish is one of the important requirements in the machining process. This paper describes mathematically the effect of cutting parameters on surface roughness in end milling process. The quadratic model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using the response surface methodology (RSM). Design of experiments approach was employed in developing the surface roughness model in relation to cutting parameters. The predicted results are in good agreement with the experimental results within the specified range of cutting conditions. Experimental results showed surface roughness increases with increase in the cutting speed, feed rate, and the axial depth of cut.

scholarly journals Experimental Study on Drilling MDF with Tools Coated with TiAlN and ZrN

Materials ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 386 ◽  
Author(s):  
Krzysztof Szwajka ◽  
Joanna Zielińska-Szwajka ◽  
Tomasz Trzepiecinski
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tool ◽  
Thrust Force ◽  
Medium Density Fiberboard ◽  
Cutting Speed ◽  
Piezoelectric Sensor ◽  
Maximum Temperature ◽  
Drilling Process ◽  
Aesthetic Appearance

There is increasing use of wood-based composites in industry not only because of the shortage of solid wood, but above all for their better properties such as: strength, aesthetic appearance, etc., compared to wood. Medium density fiberboard (MDF) is a wood-based composite that is widely used in the furniture industry. The goal of the research conducted was to determine the effect of the type of coating on the drill cutting blades on the value of thrust force (Ft), cutting torque (Mc), cutting tool temperature (T) and surface roughness of the hole in drilling MDF panels. In the tests, three types of carbide drills (HW) were used: not coated, TiAlN coated and ZrN coated. The measurement of both the thrust force and the cutting torque was carried out using an industrial piezoelectric sensor. The temperature of the cutting tool in the drilling process was measured using an industrial temperature measurement system using a K-type thermocouple. It was found that the value of the maximum temperature of the tool in the drilling process depends not only on the cutting speed and feed rate, but also on the type of coating of the cutting tool. The value of both the cutting torque and the thrust force is significantly influenced by the value of the feed rate and the type of drill coating. The effect of varying plate density on the surface roughness of the hole and the variation of the value of the thrust force is also discussed. The results of the investigations were statistically analyzed using a multi-factorial analysis of variance (ANOVA).

scholarly journals Optimization of Surface Roughness in Drilling Medium-Density Fiberboard with a Parallel Robot

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Elmas Aşkar Ayyıldız ◽  
Mustafa Ayyıldız ◽  
Fuat Kara
Keyword(s):  
Surface Roughness ◽  
Medium Density Fiberboard ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Parallel Robot ◽  
Medium Density ◽  
Taguchi Technique ◽  
Quadratic Regression ◽  
Drilling Parameters ◽  
Optimal Surface

This study focuses on the examination of the effect of cutting parameters on surface roughness when drilling medium-density fiberboard (MDF) with a parallel robot. Taguchi technique was applied to find the optimum drilling parameters and, later, the drilling processing. Experimental layout was established using the Taguchi L18 orthogonal array, and experimental data were examined via a statistical analysis of variance (ANOVA). Experimental results were performed by multiple regression analysis (linear and quadratic). Correlation coefficient (R2) was found 99.46% for surface roughness with the quadratic regression model. By the Taguchi analysis, the optimum values for the surface roughness were found to be a point angle of 118°, a cutting speed of 47.1 m/min, and a feed rate of 0.01 mm/rev. The optimization outcomes presented that the Taguchi technique had been successfully performed to decide the optimal surface roughness of the MDF in the drilling.

scholarly journals ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness

2017 ◽  
Vol 13 (2) ◽  
Author(s):  
Shakir M Mousa
Keyword(s):  
Surface Roughness ◽  
Orthogonal Array ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Quality Level ◽  
Work Piece ◽  
Signal To Noise ◽  
Taguchi Orthogonal Array ◽  
Input Parameters ◽  
Noise Ratio

Abstract   Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment (DOE) and response surface methodology (RSM).These six input parameters in this research were optimized  for all input parameters to improve the surface layer for work piece by using signal-to-noise ratio technique. The obtained results showed that all six input parameters have an influence on the change in surface roughness(∆Ra). In addition, the results showed that the surface roughness of the work piece decreased from 1.130 to 0.370µm that means high level of improvement in the change of surface roughness (0.760)µm. Keywords: MAF process, MINITAB software, parameters, Signal-to-Noise ratio, surface roughness, Taguchi orthogonal array.

Surface Roughness Prediction Model in Machining of 34CrMo4 Steel with Several Tools Using Response Surface Methodology

2012 ◽  
Vol 445 ◽  
pp. 90-95
Author(s):  
Hamed Barghikar ◽  
Amin Poursafar ◽  
Abbas Amrollahi
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Mean Values ◽  
Roughness Model ◽  
34Crmo4 Steel

The surface roughness model in the turning of 34CrMo4 steel was developed in terms of cutting speed, feed rate and depth of cut and tool nose radius using response surface methodology. Machining tests were carried out using several tools with several tool radius under different cutting conditions. The roughness equations of cutting tools when machining the steels were achieved by using the experimental data. The results are presented in terms of mean values and confidence levels.The established equation and graphs show that the feed rate and cutting speed were found to be main influencing factor on the surface roughness. It increased with increasing the feed rate and depth of cut, but decreased with increasing the cutting speed, respectively. The variance analysis for the second-order model shows that the interaction terms and the square terms were statistically insignificant. However, it could be seen that the first-order affect of feed rate was significant while cutting speed and depth of cut was insignificant.The predicted surface roughness model of the samples was found to lie close to that of the experimentally observed ones with 95% confident intervals.

Taguchi optimization of surface roughness in the turning of Hastelloy C22 super alloy using cryogenically treated ceramic inserts

2020 ◽  
Vol 234 (19) ◽  
pp. 3826-3836
Author(s):  
Sıtkı Akincioğlu ◽  
Hasan Gökkaya ◽  
Gülşah Akincioğlu ◽  
Meltem A Karataş
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cryogenic Treatment ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Deep Cryogenic Treatment ◽  
Taguchi Optimization ◽  
Factors Affecting ◽  
Treatment Type ◽  
Super Alloy

Cryogenic treatment has been used in recent years to improve the performance of cutting tools. This study evaluated the machinability of a nickel–molybdenum-based super alloy using cryogenically treated (–80 ℃ and –145 ℃) ceramic inserts under dry turning conditions. Three cutting speeds (350, 400, and 450 m/min), three feed rates (0.1, 0.2, and 0.3 mm/rev), and a 1-mm fixed cutting depth were used in the turning tests. Experiments were conducted using the Taguchi orthogonal array L27 design. The factors affecting the surface roughness (Ra) were determined via analysis of variance. The effect of cryogenic treatment type (shallow and deep), cutting speed, and feed rate on surface roughness was investigated. Results of the analysis determined that the feed rate was the major parameter that affected surface roughness and that the deep cryogenic treatment was more effective. The regression analysis confirmed that the experimental results and the predicted values were within the 95% confidence interval. The most effective parameter affecting the surface roughness was feed rate at a contribution of 57.9%. The contribution of the cutting tool type to the surface roughness was 28.5%. The results obtained showed that the surface roughness can be optimized for turning the Hastelloy c22 super alloy with the Taguchi method.

Investigation of the effect of cutting parameters on the milling process of cryogenically treated aluminum alloy with cryogenically treated and untreated inserts, using the Taguchi and Gray Relational Analysis methods

2021 ◽  
Author(s):  
Gürcan Samtaş ◽  
Berat Serhat Bektaş
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Milling Process ◽  
Gray Relational Analysis ◽  
Taguchi Optimization ◽  
Relational Analysis ◽  
Cutting Insert ◽  
Cutting Inserts

Abstract The aluminum 6061 alloy is commonly employed in the automotive industry in the manufacture of rims, panels and even the chasses of vehicles and has excellent machinability. In this study, the surface of the cryogenically processed aluminum 6061-T651 alloy was milled using both untreated and cryogenically treated TiN-TiCN-Al2O3-coated cutting inserts. The Taguchi L18 orthogonal array was chosen as the experimental design. As the cutting parameters in the experiments, two different cutting inserts (untreated and cryogenically treated, TiN-TiCN-Al2O3-coated), three different cutting speeds (250, 350 and 450 m/min) and three different feed rates (0.15, 0.30 and 0.45 mm/rev) were used. After each experiment, the surface roughness and wear values of the cutting inserts were measured, the latter after repeating the experiment five times. Wear and roughness values were optimized using the Taguchi method. Additionally, Gray Relational Analysis (GRA) was used for the combined optimization of wear and roughness values. The optimized findings determined using Taguchi optimization for minimum surface roughness were the cryogenically treated cutting insert, 250 m/min cutting speed and 0.45 mm/rev feed rate. The optimized findings for wear were the cryogenically treated cutting insert, 350 m/min cutting speed and 0.30 mm/rev feed rate. In the optimization with GRA, the common optimum parameters for surface roughness and wear were the cryogenically treated cutting insert, 250 m/min cutting speed and 0.15 mm/rev feed rate. According to the Taguchi and GRA results, the cryogenically treated cutting inserts performed the best in terms of minimum wear and surface roughness. The Gray-based Taguchi methodology proposed in this study was found to be effective in solving the decision-making problem in multi-specific results as wear and surface roughness.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

Sign in / Sign up

Export Citation Format

Share Document