Prediction of Cutting Forces during Turning PA66 GF-30 Glass Fiber Reinforced Polyamide by Soft Computing Techniques

2013 ◽  
Vol 766 ◽  
pp. 37-58 ◽  
Author(s):  
Nikolaos A. Fountas ◽  
Ioannis Ntziantzias ◽  
John Kechagias ◽  
Aggelos Koutsomichalis ◽  
João Paulo Davim ◽  
...  
Keyword(s):  
Glass Fiber ◽  
Cutting Force ◽  
Soft Computing ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Fiber Reinforced ◽  
Glass Fiber Reinforced ◽  
Soft Computing Techniques ◽  
Cutting Force Components ◽  
Force Components

In the present paper the influence of the main cutting parameters on process performance during longitudinal turning of PA66 GF-30 Glass Fiber Reinforced Polyamide is investigated. The selected cutting parameters are cutting speed and feed-rate whilst depth of cut is kept constant. As outputs (responses), cutting force components Ft, FV and Fr were selected. Test specimens in the form of round bars and cemented carbide cutting tool were used during the experimental process. Fifteen experiments were conducted having all different combinations of cutting parameter values. Analysis of Variance (ANOVA), statistical approaches and soft computing techniques (artificial neural network) were applied in order to formulate stochastic models for relating the responses with main cutting parameters. The results obtained, indicate that the proposed soft computing techniques can be effectively used to predict the cutting force components (Ft, FV and Fr) thus; facilitating decision making during process planning since costly and time-consuming experimentation can be avoided.

Modelling and Analysis of Wear Prediction in Machining of Nano Based GFRP Composites Using RSM

2015 ◽  
Vol 20 ◽  
pp. 3-11
Author(s):  
A. Saravanapandi Solairajan ◽  
S. Alexraj ◽  
P. Vijaya Rajan ◽  
Godwin Jose
Keyword(s):  
Glass Fiber ◽  
Unsaturated Polyester ◽  
Glass Fibers ◽  
Cutting Speed ◽  
Polycrystalline Diamond ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Fiber Reinforced ◽  
Gfrp Composites ◽  
Glass Fiber Reinforced

Glass fiber reinforced composite material was fabricated using E-glass fiber with unsaturated polyester resin. In Glass Fiber Reinforced Plastic (GFRP) composites, the matrix of polymer is reinforced with glass fibers. The surface quality and dimensional precision significantly affect the parts during their suitable life, particularly in cases where the components come in contact with other elements or materials. In the current study, GFRP is machined with two cases i.e. with and without Nano combinations in lathe. These machining studies were carried out on lathe using three different cutting tools: namely Carbide (K-20), Cubic Boron Nitrate (CBN) and Polycrystalline Diamond (PCD). The cutting parameters considered were cutting speed, feed, and depth of cut. Surface Finish is the most important parameter measured by main spindle and compares the value with another. A second order mathematical model in terms of cutting parameters was developed using RSM. The results specify the developed model is suitable for prediction of surface roughness in machining of GFRP composites.

An Experimental Investigation of the Cutting Force in High Speed Ball-End Rough Milling of Cr12MoV

2012 ◽  
Vol 426 ◽  
pp. 193-196
Author(s):  
Zi Ye Liu ◽  
Chuan Zhen Huang ◽  
Xin Qiang Zhuang ◽  
Bin Zou ◽  
Han Lian Liu ◽  
...  
Keyword(s):  
Cutting Force ◽  
High Speed ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Wave Form ◽  
Range Analysis ◽  
Cutting Force Components ◽  
Rough Milling ◽  
Force Components

An orthogonal test was carried out so as to analyze the cutting force in high speed rough milling with ball-end cutting tools. The wave form of the cutting force components was analyzed. The range analysis was performed to investigate the effect of cutting parameters on the cutting force. The analysis results show that the depth of cut and feed rate have the most significant effect on the resultant force. An empirical equation to describe the resultant cutting force was developed.

Investigation of optimum cutting parameters and tool radius in turning glass-fiber-reinforced composite material

2016 ◽  
Vol 23 (1) ◽  
pp. 85-92 ◽  
Author(s):  
Ahmet Yardimeden
Keyword(s):  
Surface Roughness ◽  
Composite Materials ◽  
Glass Fiber ◽  
Cutting Force ◽  
Cutting Parameters ◽  
Machining Parameters ◽  
Fiber Reinforced ◽  
Fiber Reinforced Composite ◽  
Reinforced Composite ◽  
Glass Fiber Reinforced

AbstractGlass-fiber-reinforced composite materials (GFRPs) are used widely in various fields of engineering. Turning is the principal process conducted on these materials for obtaining minimum surface roughness. Machining of GFRP materials is different from traditional style due to their inhomogeneous and anisotropic structures. Optimum machining parameters for specific GFRP materials need to be ascertained for perfect machining. In this study, the influence of cutting parameters and insert radius on the cutting force and surface roughness of GFRP material during machining was investigated. For measuring main cutting force, a three-component piezoelectric crystal type of dynamometer was used. Cutting force and surface roughness were experimentally measured through longitudinal axes of the GFRP material. Through this study, it was observed that high cutting speeds and low feed rates provide the best surface quality in the turning process of GFRP composite materials.

scholarly journals Trochoidal Milling and Neural Networks Simulation of Magnesium Alloys

Materials ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2070 ◽  
Author(s):  
Ireneusz Zagórski ◽  
Monika Kulisz ◽  
Mariusz Kłonica ◽  
Jakub Matuszak
Keyword(s):  
Neural Networks ◽  
Cutting Force ◽  
Magnesium Alloys ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Milling Process ◽  
Machining Parameters ◽  
Cutting Force Components ◽  
Multilayered Perceptron ◽  
Force Components

This paper set out to investigate the effect of cutting speed vc and trochoidal step str modification on selected machinability parameters (the cutting force components and vibration). In addition, for a more detailed analysis, selected surface roughness parameters were investigated. The research was carried out for two grades of magnesium alloys—AZ91D and AZ31—and aimed to determine stable machining parameters and to investigate the dynamics of the milling process, i.e., the resulting change in the cutting force components and in vibration. The tests were performed for the specified range of cutting parameters: vc = 400–1200 m/min and str = 5–30%. The results demonstrate a significant effect of cutting data modification on the parameter under scrutiny—the increase in vc resulted in the reduction of the cutting force components and the displacement and level of vibration recorded in tests. Selected cutting parameters were modelled by means of Statistica Artificial Neural Networks (Radial Basis Function and Multilayered Perceptron), which, furthermore, confirmed the suitability of neural networks as a tool for prediction of the cutting force and vibration in milling of magnesium alloys.

scholarly journals Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6

2018 ◽  
Vol 14 (1) ◽  
pp. 67-76
Author(s):  
Mohanned Mohammed H. AL-Khafaji
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Thickness Ratio ◽  
Depth Of Cut ◽  
Feed Force ◽  
Machining Force ◽  
Force Components

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).

Modelling and Analysis of Relationship between Cutting Parameters Surface Roughness and Cutting Forces Using Response Surface Methodology when Hard Turning with Coated Ceramic Inserts

2016 ◽  
Vol 686 ◽  
pp. 19-26 ◽  
Author(s):  
Ildikó Maňková ◽  
Marek Vrabeľ ◽  
Jozef Beňo ◽  
Mária Franková
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Cutting Force ◽  
Response Surface ◽  
Hard Turning ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Oxide Ceramic ◽  
Cutting Force Components ◽  
Force Components

Experimental research and modeling in the field of turning hardened bearing steel with hardness of 62 HRC using TiN coated mixed oxide ceramic inserts is presented. The main objective of the article is investigation the relationship between cutting parameters (cutting speed and feed rate) and output machining variables (surface roughness and cutting force components) through the response surface methodology (RSM). The mathematical model of the effect of process parameters on the cutting force components and surface roughness is presented. Moreover, the influence of TiN coating on above mentioned variables was monitored. The design of experiment according to Taguchi L9 orthogonal matrix (32) was applied for trials. Pearson´s correlation matrix was used to examine the dependence between the factors (f, vc) and the machining variables (surface roughness and cutting force components). The results show how much surface roughness and cutting force components is influenced by cutting speed and feed in hard turning with coated ceramics.

An Experimental Study on Cutting Forces in the Threading and the Side Cut Turning With Coated and Uncoated Grades

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Firat Kafkas
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
Three Dimensional ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Dynamic Force ◽  
Low Alloy Steels ◽  
Workpiece Material ◽  
Cutting Force Components ◽  
Force Components

The objective of this study is to obtain the cutting force components on the threading insert. The cutting force data used in the analysis are measured by a three-dimensional dynamic force dynamometer. The AISI 4140 and AISI 4340 low alloy steels are selected for the experiment on the threading and the side cut turning. The inserts used for testing is the TiAlN coated and uncoated grades. LT22NR35ISO type insert is used in the experiment. During the experiments, no cutting fluid and a constant spindle speed is used. The thread pitch and the depth of cut were kept fixed at 3.5 mm and 0.05 mm for the radial feed per pass, respectively. The study emphasizes on the effects on the workpiece material and the cutting tool grade of the cutting force components that occur during the threading. Also, these results are compared with the findings that are obtained during the side cut turning. It is determined that the measured primary cutting and radial forces during the threading are approximately three times bigger than those during the side cut turning, although feed forces during the threading are approximately 30 times lower compared with the side cut turning. The TiAlN coated WC/Co grade shows the best performance with respect to the cutting force components. The specific cutting forces are determined in order to understand the interference of chips that occur during the threading. With the increase in the cumulative radial feed, the corresponding specific cutting forces become higher. It is reasoned that the difference in the specific cutting forces results from the alteration of the interference of the flowing chips. The specific cutting forces decrease in the beginning of the threading and then increases with the cumulative radial feed. The results show that the interference of the chip flow influences the threading force components to a very large extent.

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