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.

scholarly journals PENGARUH PARAMETER MENGGURDI BERTAHAP TERHADAP TERBENTUKNYA RASIO DELAMINASI BAIK PADA SISI MASUK MAUPUN SISI KELUAR LUBANG

2019 ◽  
Vol 9 (2) ◽  
pp. 245
Author(s):  
Irwan Kurniawan
Keyword(s):  
Orthogonal Array ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Anova Analysis ◽  
Taguchi Orthogonal Array ◽  
Noise Ratio

Delaminasi merupakan salah satu jenis kerusakan  kritis pada material Komposit. Delaminasi terjadi akibat sebagian dari benda kerja tidak terpotong secara sempurna akan tetapi dilakukan proses pemotongan dengan cara memberikan penekanan melalui pahat gurdi ke material, justru yang terjadi deformasi plastis disebabkan mekanisme penekanan, pada umumnya kondisi seperti ini terjadi pada material  lunak yang memiliki mampu mesin yang rendah dan cenderung menghasilkan cacat seperti delaminasi baik pada bagian masuk (Entrance) maupun keluar lubang (Exit).  penggunaan geometri pahat yang dimodifikasi bertingkat bukanlah  merupakan  kondisi yang  terjadi sebenarnya. Untuk saat ini, kondisi tersebut baru dapat dipenuhi dalam  skala laboratorium, untuk  kondisi sebenarnya penggunaan  metoda menggurdi Step drilling ( Page Drilling Cycle) yang paling memungkinkan  Oleh karena itu pada penelitian ini difokuskan untuk melihat peluang penggunaan metoda  menggurdi bertahap. Dengan menggunakan Rancangan  Metode Taguchi Orthogonal Array L36 pengamatan dilakukan. Hasilnya dianalisa dengan  menggunakan metoda Signal-to-Noise Ratio (S/N ratio) dan ANOVA (Analysis of Variances).  Hasil dari   S/N ratio mengindikasikan bahwa gerak makan kontribusinya sangat kecil untuk menggurangi delaminasi dalam  suatu sistem pemotongan kemungkinan ini disebakan karena gerak makan yang diberikan itu merupakan  rentang yang kecil secara teoritis tidak akan berpengaruh besar terhadap terbentukanya delaminasi 

scholarly journals Simulation Effects of Surface Geometry and Water Optical Properties on Hydrographic Lidar Returns

2020 ◽  
Vol 237 ◽  
pp. 08020
Author(s):  
Song Yang ◽  
Qian Sun ◽  
Yongchao Zheng
Keyword(s):  
Surface Roughness ◽  
Optical Properties ◽  
Water Surface ◽  
Signal To Noise Ratio ◽  
Surface Geometry ◽  
Signal To Noise ◽  
Noise Ratio

. Water LiDAR model was applied to simulate the returned waveforms of hydrographic LiDAR considering the effects of surface geometry and water optical properties. The signal to noise ratio(SNR) of bottom returned peak was considered as a criterion for performance of hydrographic LiDAR. The behavior of LiDAR was sensitive to water optical properties and it was insensitive to water surface roughness.

Evaluation of the cutting forces, the surface roughness, and the tool wear characteristics during machining of cobalt-based superalloy Haynes 188 with ceramic cutting tool

2021 ◽  
pp. 095440892110480
Author(s):  
Abdullah Altin
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Tool ◽  
Signal To Noise Ratio ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Signal To Noise ◽  
Ceramic Cutting Tool ◽  
Cutting Speeds

In this research, we had studied the sensitivity for machining of cobalt-based superalloy Haynes 188 with ceramic cutting tool. The investigation had focused on the effects of the cutting speed, on the cutting forces, and on the surface roughness based on Taguchi’s experimental design. The effects of machining parameters were determined using Taguchi’s L27 orthogonal array. The signal-to-noise ratio was calculated for the average of surface roughness and the cutting forces, and the smaller were used to determine the optimal cutting conditions. The analysis of variance and the signal-to-noise ratio had effects on the parameters on both surface roughness and cutting. Three different types of cutting tools had been used in the experiment, namely KYON 4300, KYS 25, and KYS 30. The cutting force of Fz was considered to be the main cutting force. Depending on the material which had been used as cutting tool, the Fz had the lowest cutting speed and the lowest surface roughness with the KYS25 ceramic tool. The cutting force and the surface roughness of KYON 4300 cutting tool had shown better performance than other cutting tools. The flank wear and notch were found to be more effective in the experiments. The long chips were removed at low and medium cutting speeds, while the sawdust with one edge and narrow pitch at high cutting speeds was obtained.

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.

Effect of Different Laser Welding Parameter on Welding Strength in Polymer Transmission Welding Using Semiconductor

2020 ◽  
Vol 38 (5A) ◽  
pp. 761-768
Author(s):  
Farah M. Shakera ◽  
Mohannad M. Al-Khafaji ◽  
Kadhim A. Hubeatir
Keyword(s):  
Process Parameters ◽  
Welding Speed ◽  
Orthogonal Array ◽  
Signal To Noise Ratio ◽  
Spot Size ◽  
Welding Parameter ◽  
Signal To Noise ◽  
Laser Transmission Welding ◽  
Taguchi Orthogonal Array ◽  
Welding Strength

In this work, the diode laser (810μm wavelength) was used for laser transmission welding application on PMMA (polymethylmethacrylate). The welding was done between opaqueness and transparent with thickness 2 mm and 2.57 mm, respectively. The effects of different process parameters, laser speed, spot size and force with different values (5, 15, 20 mm/min), (2, 2.5, 3mm) and (2, 6, 10 N) respectively were used to study their effect on weld width and strength. L9 Taguchi orthogonal array has been used to design the experiments and optimize the result. The result of the signal to noise ratio shows that, the width of welding decrease with increasing both the welding speed and the spot size while it was increased with increasing the force on the sample. The narrower width observed at speed (20mm/min), spot size (3mm), and force (2N). Also, the best strength was found at speed (15 mm/min), spot size (2.5mm), and force (10N).

scholarly journals High Speed Machining for Enhancing the AZ91 Magnesium Alloy Surface Characteristics Influence and Optimisation of Machining Parameters

2022 ◽  
Vol 72 (1) ◽  
pp. 105-113
Author(s):  
Vikas Marakini ◽  
Srinivasa P Pai ◽  
Uday K Bhat ◽  
Dinesh Thakur Singh ◽  
Bhaskar P Achar
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Signal To Noise Ratio ◽  
Surface Characteristics ◽  
Taguchi Design ◽  
Machining Parameters ◽  
Signal To Noise ◽  
Relational Analysis ◽  
Noise Ratio ◽  
Grey Relational

In this study, optimum machining parameters are evaluated for enhancing the surface roughness and hardness of AZ91 alloy using Taguchi design of experiments with Grey Relational Analysis. Dry face milling is performed using cutting conditions determined using Taguchi L9 design and Grey Relational Analysis has been used for the optimization of multiple objectives. Taguchi’s signal-to-noise ratio analysis is also performed individually for both characteristics and grey relational grade to identify the most influential machining parameter affecting them. Further, Analysis of Variance is carried to see the contribution of factors on both surface roughness and hardness. Finally, the predicted trends obtained from the signal-to-noise ratio are validated using confirmation experiments. The study showed the effectiveness of Taguchi design combined with Grey Relational Analysis for the multi-objective problems such as surface characteristics studies.

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 Analysis of Closed Loop Production System Using Orthogonal Array and Integer Programming Optimization

2019 ◽  
Vol 38 (3) ◽  
pp. 851-866 ◽  
Author(s):  
Abdul Salam Khan
Keyword(s):  
Production System ◽  
Orthogonal Array ◽  
Closed Loop ◽  
Production Systems ◽  
Signal To Noise Ratio ◽  
Raw Material ◽  
Signal To Noise ◽  
Manufacturing Cells ◽  
Control Variables ◽  
Noise Ratio

Sustainable production systems require optimal utilization of resources. Raw material acquisition is one of the costly processes in a production system. EOL (End-of-Life) products re-manufacturing through reverse logistics can help in decreasing excessive raw material cost. In this study, we consider production system of closed loop supply chain in which both forward and reverse production systems are active. DOE (Design of Experiments) methodology is incorporated which is a statistical approach adopted in dealing with complex workplace problems. We employ L9 orthogonal array using Taguchi experiment in Minitab 17 and DOE for plotting the results. Dependent variables used in this study are productivity, P (number of forward and reverse products produced per period) and quality accuracy of product (measured in percent deviation from reference standards). A trade-off analysis between the control variables is presented on the basis of SNR (Signal to Noise Ratio). Control variables used in the analysis are tools employed in production system (tu), number of machines being used (m) and dedicated manufacturing cells (dc). We use three levels of analysis for each control factor. Optimum result conditions are calculated using signal to noise ratio with larger-the-better-criteria as well as smaller-the-better criteria and study is concluded with main effects of the mean plots. DOE optimization analysis for productivity suggests combination set of 32, 8, and 6 for tools, machines in use and manufacturing cells, respectively. Similarly, for optimal dimensional accuracy, tools used are 24; number of machines in use is 14 with 3 manufacturing cells. All result indices are accomplished within a confidence interval of 95% with p-values less than 0.05. MILP (Mixed Integer Linear Programming) analysis considers cost function of production and transportation between tools, machines and levels and Taguchi based experimental findings are validated by mathematical optimization findings.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

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