Application of Teaching

2015 ◽  
Vol 2 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade
Keyword(s):  
Tool Path ◽  
End Milling ◽  
Optimization Technique ◽  
Milling Process ◽  
Parameters Optimization ◽  
Machining Parameters ◽  
Machining Processes ◽  
Conflicting Objectives ◽  
Advanced Machining ◽  
Teaching Learning

Recently advanced machining processes are widely used by manufacturing industries in order to produce high quality precise and very complex products. These advanced machining processes involve large number of input parameters which may affect the cost and quality of the products. Selection of optimum machining parameters in such advanced machining processes is very important to satisfy all the conflicting objectives of the process. This algorithm is inspired by the teaching-learning process and it works on the effect of influence of a teacher on the output of learners in a class. This paper presents the application of Response Surface Methodology coupled with newly developed advanced algorithm Teaching Learning Based Optimization Technique (TLBO) is applied for the process parameters optimization for ball end milling process on Inconel 718 cantilevers. The machining and tool related parameters like spindle speed, milling feed, workpiece thickness and workpiece inclination with tool path orientation are optimized with considerations of multiple response like deflection, surface roughness, and micro hardness of plate.

scholarly journals Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5326
Author(s):  
Andrés Sio-Sever ◽  
Erardo Leal-Muñoz ◽  
Juan Manuel Lopez-Navarro ◽  
Ricardo Alzugaray-Franz ◽  
Antonio Vizan-Idoipe ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
End Milling ◽  
Low Cost ◽  
Milling Process ◽  
Machining Process ◽  
Measuring System ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Processes ◽  
Non Invasive

This work presents a non-invasive and low-cost alternative to traditional methods for measuring the performance of machining processes directly on existing machine tools. A prototype measuring system has been developed based on non-contact microphones, a custom designed signal conditioning board and signal processing techniques that take advantage of the underlying physics of the machining process. Experiments have been conducted to estimate the depth of cut during end-milling process by means of the measurement of the acoustic emission energy generated during operation. Moreover, the predicted values have been compared with well established methods based on cutting forces measured by dynamometers.

Experimental Investigation and Parametric Optimization in Abrasive Jet Machining on NICKEL 233 Alloy Using WASPAS

2019 ◽  
Vol 18 (04) ◽  
pp. 549-561
Author(s):  
S. Rajendra Prasad ◽  
K. Ravindranath ◽  
M. L. S. Devakumar
Keyword(s):  
Parametric Optimization ◽  
Removal Rate ◽  
Optimization Technique ◽  
Machining Parameters ◽  
Abrasive Jet Machining ◽  
Process Pressure ◽  
Conflicting Objectives ◽  
Machined Parts ◽  
Optimal Setting ◽  
First Time

Decision of finest machining parameters is very essential factors in any processing of machined parts. This article presents a multi-objective optimization technique, based on WASPAS method toward optimize the machining parameters in abrasive jet machining (AJM) process: pressure, nozzle to tip distance (NTD), and average grain diameter on NICKEL 233 alloy. Three conflicting objectives, Material Removal Rate (MRR), surface roughness (Ra) and taper angle (Ta) are simultaneously considered. The proposed technique weighted aggregated product sum assessment technique is investigation of parametric optimization on AJM process. Its outcome using tool in any ranges of responses in AJM process is the optimal setting of parameters are determined through experiments illustrated. Broad usage of Aerospace industries for NICKEL 233, generating a hole of the machining data first time in this work using AJM will be useful.

Advanced Machining Processes for Micro Mold Fabrication

2012 ◽  
Vol 523-524 ◽  
pp. 1018-1023
Author(s):  
Ekkard Brinksmeier ◽  
Oltmann Riemer ◽  
Christian Robert ◽  
Sven Twardy
Keyword(s):  
End Milling ◽  
Surface Characteristics ◽  
Micro Forming ◽  
Machining Processes ◽  
Single Crystalline ◽  
Mold Making ◽  
Micro Parts ◽  
Advanced Machining ◽  
Mold Fabrication ◽  
Forming Tools

This paper presents two alternative approaches in mold making for micro forming processes. The quality of formed micro parts is mainly dominated by the process parameters and the surface characteristics of the applied forming tools. Forming dies with advanced micro structures can improve the result of forming processes compared to tools with smooth surfaces. Here an approach of micro ball end milling is described to generate the macro geometry as well as an engineered surface texture on micro forming tools in one machining step. In addition to the surface topography, the die material has a decisive influence on the forming result and durability of the forming tool. Therefore single crystalline diamond represents an promissing material for forming tools, because of its unique material characteristics. On the other hand single crystalline diamond requires unreasonable high efforts for its geometrical shaping. Therefore, this paper will introduce a new approach to machine single crystalline diamond by thermo-chemical material removal.

Investigation on Chip Morphology and Surface Quality in High-Speed Ball-End Milling of Inconel 718

2010 ◽  
Vol 443 ◽  
pp. 353-358 ◽  
Author(s):  
Harshad A. Sonawane ◽  
Suhas S. Joshi
Keyword(s):  
Surface Quality ◽  
Inconel 718 ◽  
High Speed ◽  
End Milling ◽  
Chip Morphology ◽  
Helix Angle ◽  
Processing Parameters ◽  
Milling Process ◽  
Machining Parameters ◽  
Ball End Milling

The ball end milling process, commonly used for generating complex shapes, involves continuous variation in the uncut chip dimensions, which depends on the cutter geometry and the machining parameters. The proposed analytical model evaluates the undeformed and the deformed chip dimensions including chip length, width and thickness. The undeformed and deformed chip dimensions, is a function of cutter rotation angle, instantaneous cutter radius, helix angle, and other processing parameters. The surface quality, in the form of surface roughness, during high-speed ball end milling of Inconel 718 is also analysed in this paper.

Modeling & Analysis of End Milling Process Parameters Using Artificial Neural Networks

2014 ◽  
Vol 592-594 ◽  
pp. 2733-2737 ◽  
Author(s):  
G. Harinath Gowd ◽  
K. Divya Theja ◽  
Peyyala Rayudu ◽  
M. Venugopal Goud ◽  
M .Subba Roa
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Artificial Neural ◽  
End Milling Process

For modeling and optimizing the process parameters of manufacturing problems in the present days, numerical and Artificial Neural Networks (ANN) methods are widely using. In manufacturing environments, main focus is given to the finding of Optimum machining parameters. Therefore the present research is aimed at finding the optimal process parameters for End milling process. The End milling process is a widely used machining process because it is used for the rough and finish machining of many features such as slots, pockets, peripheries and faces of components. The present work involves the estimation of optimal values of the process variables like, speed, feed and depth of cut, whereas the metal removal rate (MRR) and tool wear resistance were taken as the output .Experimental design is planned using DOE. Optimum machining parameters for End milling process were found out using ANN and compared to the experimental results. The obtained results provβed the ability of ANN method for End milling process modeling and optimization.

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