Experimental Investigation on Prediction of Hole Quality Characteristics of Aluminum Matrix Composite (AMC225xe)

2012 ◽  
Vol 622-623 ◽  
pp. 1305-1309 ◽  
Author(s):  
Sureshkumar Manickam Shanmugasundaram ◽  
Lakshmanan Damodhiran ◽  
Murugarajan Angamuthu
Keyword(s):  
Experimental Investigation ◽  
Matrix Composite ◽  
Process Parameters ◽  
Feed Rate ◽  
Aluminum Matrix ◽  
Aluminum Matrix Composite ◽  
Quality Characteristics ◽  
Hole Quality ◽  
Machining Properties

Wide spread applications of composite materials have been significantly growing in aerospace, naval, space, and automotive industries. Drilling of such materials is a challenging task because of differential machining properties and checking the quality of hole is significantly a great attention. In this paper, experimental investigation on prediction of hole quality characteristics of aluminum matrix composite (AMC225xe) during drilling process. The influence of process parameters such as speed, feed rate and coolant flow rate on the surface finish and circularity were investigated during the experimentation. The experiments were conducted according to the Taguchi’s L9 array design using process parameters. The quality of the hole characteristics were measured using roughness tester and CMM. Regression analysis has been carried out for prediction of hole quality characteristics from the experimentation. It is observed that the predicted results are good correlation with measured values. Also, the results indicate that the feed rate is the most influencing parameter for drilling of AMC225xe.

Experimental investigation on hole quality in drilling of composite pipes

2018 ◽  
Vol 42 (2) ◽  
pp. 147-155 ◽  
Author(s):  
Rajkumar Tibadia ◽  
Koustubh Patwardhan ◽  
Dhrumil Shah ◽  
Dinesh Shinde ◽  
Rakesh Chaudhari ◽  
...  
Keyword(s):  
Experimental Investigation ◽  
Feed Rate ◽  
Industrial Applications ◽  
Spindle Speed ◽  
Drilling Process ◽  
Hole Quality ◽  
Microstructural Investigation ◽  
Circularity Error ◽  
Composite Pipes

In recent years, the major reason for the rejection of composite pipes in industrial applications is due to the poor quality of the drilled hole. This paper investigates the effect of drilling process parameters on the hole quality in composite pipes made of an aluminium core surrounded by polyethylene layers. An empirical model is designed for the two input variables using response surface methodology (central composite design). An experimental investigation is carried out to study the effect of spindle speed and feed rate on quality of drilled holes, especially circularity error. It is observed that a moderate spindle speed and low feed rate are most effective in minimizing the circularity error. Microstructural investigation of drilled hole surface is also carried out using scanning electron microscopy (SEM).

Optimization of Stirring Parameters Through Numerical Simulation for the Preparation of Aluminum Matrix Composite by Stir Casting Process

2010 ◽  
Vol 132 (6) ◽  
Author(s):  
Hai Su ◽  
Wenli Gao ◽  
Hui Zhang ◽  
Hongbo Liu ◽  
Jian Lu ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Flow Pattern ◽  
Matrix Composite ◽  
Process Parameters ◽  
Flow Behavior ◽  
Aluminum Matrix ◽  
Suitable Condition ◽  
Casting Process ◽  
Stir Casting ◽  
Aluminum Matrix Composite

The flow behavior of the fluid has a significant effect on the particle distribution in the solid-liquid mixing vessel. The stir casting process is generally conducted in a closed crucible, in which the flow pattern is invisible. Therefore, numerical simulation is a forceful tool to guide the experimental research. In the present study, the fluid flow in the stirred crucible during stir casting has been simulated using finite element method. The effects of some important stirring process parameters, such as the blade angle, rotating speed, the diameter of the impeller, and the stirrer geometry, on the flowing characteristics of the molten matrix have been investigated in order to achieve the effective flow pattern to uniformly disperse the ceramic particles in the molten matrix. The simulation results show that the process parameters have significant effects on the flow behavior of the fluid in the stirred crucible. The various combinations of these parameters are beneficial to generate a suitable condition for the composite casting. Further experimental investigation reveals that the present work can provide a guide for the industrial preparation of aluminum matrix composite with a uniform particle reinforcement distribution by stir casting process.

scholarly journals Tool Wear Prediction Based on Artificial Neural Network during Aluminum Matrix Composite Milling

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5798
Author(s):  
Martyna Wiciak-Pikuła ◽  
Agata Felusiak-Czyryca ◽  
Paweł Twardowski
Keyword(s):  
Tool Wear ◽  
Matrix Composite ◽  
Model Development ◽  
Aluminum Matrix ◽  
Aluminum Matrix Composite ◽  
Wear Prediction ◽  
Tool Wear Prediction ◽  
Al2o3 Reinforcement ◽  
Artificial Neural

This article deals with the phenomenon of tool wear prediction in face milling of aluminum matrix composite materials (AMC), class as hard-to-cut materials. Artificial neural networks (ANN) are one of the tools used to predict tool wear or surface roughness in machining. Model development is applicable when regression models do not give satisfactory results. Because of their mechanical properties based on SiC or Al2O3 reinforcement, AMCs are applied in the automotive and aerospace industry. Due to these materials’ abrasive nature, a three-edged end mill with diamond coating was selected to carry out milling tests. In this work, multilayer perceptron (MLP) models were used to predict the tool flank wear VBB and tool corner wear VBC during milling of AMC with 10% SiC content. The signals of vibration acceleration and cutting forces were selected as input to the network, and the tests were carried out with three cutting speeds. Based on the analysis of the developed models, the models with the best efficiency were selected, and the quality of wear prediction was assessed. The main criterion for evaluating the quality of the developed models was the mean square error (MSE) in order to compare measured and predicted value of tool wear.

scholarly journals Experimental Investigation, Modeling and Optimization of Circularity, Cylindricity and Surface Roughness in Drilling of PMMA Using ANN and ANOVA

2020 ◽  
Vol 57 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Florin Susac ◽  
Felicia Stan
Keyword(s):  
Surface Roughness ◽  
Experimental Investigation ◽  
Feed Rate ◽  
Quality Characteristics ◽  
Spindle Speed ◽  
Hole Quality ◽  
Modeling And Optimization ◽  
Taguchi Design Of Experiments ◽  
The Impact ◽  
Cylindricity Error

In this paper, experimental investigation, modeling and optimization of the drilling of PMMA are performed using the Taguchi Design of Experiments (DOE), analysis of variance (ANOVA) and artificial neural networks (ANN) methods. Drilling experiments were conducted on PMMA to assess the impact of process parameters (drill diameter, spindle speed, and feed rate) on the hole-quality characteristics (surface roughness, circularity error, and cylindricity error). ANOVA was performed to identify the drilling parameters that have a statistically significant influence on the hole-quality characteristics. A predictive model for the hole-quality characteristics was derived using a four-layer ANN with a backpropagation algorithm and a sigmoidal transfer function at the hidden layers. The ANN model was able to accurately predict the hole-quality parameters with the absolute mean relative errors of the testing data in the limits of 3 to 7%. Based on the experimental results and analytical modeling, it was found that drilling of PMMA requires lower spindle speed and high feed rate when the integrity of the drill hole is the main quality criterion.

Macro-Micro Relationship of Dimensional Changing Behavior of Aluminum Matrix Composite

2020 ◽  
Author(s):  
Deng Gong ◽  
Longtao Jiang ◽  
Youfang Cao ◽  
Yuanzi Zhou ◽  
Tingting Guo ◽  
...  
Keyword(s):  
Matrix Composite ◽  
Aluminum Matrix ◽  
Aluminum Matrix Composite ◽  
Relationship Of

Nanocarbon in the Structure of a Hypereutectic Aluminum-Matrix Composite

2020 ◽  
Vol 14 (4) ◽  
pp. 668-672 ◽  
Author(s):  
A. S. Aronin ◽  
I. M. Aristova ◽  
G. E. Abrosimova ◽  
V. V. Vasenev ◽  
V. N. Mironenko
Keyword(s):  
Matrix Composite ◽  
Aluminum Matrix ◽  
Aluminum Matrix Composite

High strength particulate aluminum matrix composite design: Synergistic strengthening strategy

2021 ◽  
Vol 25 ◽  
pp. 100697
Author(s):  
Chenwei Shao ◽  
Calvin Lo ◽  
Kapil Bhagavathula ◽  
André McDonald ◽  
James Hogan
Keyword(s):  
Matrix Composite ◽  
Aluminum Matrix ◽  
High Strength ◽  
Aluminum Matrix Composite
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