scholarly journals Reducing Cycle Time of Machining a Manifold on a CNC Machine

2020 ◽  
Vol 5 (4) ◽  
pp. 37-52
Author(s):  
Rahul Aggarwal ◽  
◽  
Mehul Soni ◽  
Pranjal Singh ◽  
A K Madan
Keyword(s):  
Cycle Time ◽  
Capital Investment ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cnc Machining ◽  
Depth Of Cut ◽  
Cnc Machine ◽  
Management Level ◽  
Set Up ◽  
Machining Productivity

This report focuses on the different methods to improve productivity at the management level, at the machine shop, and of machining methods. The various parameters affecting machining productivity i.e., cycle time, set-up time, idle time, operator skill level, etc. including how CNC machining helps in optimizing these parameters are discussed and analyzed in this paper. The effect of different cutting parameters like cutting speed, feed rate, depth of cut, the effect of coolant, etc. is also examined. Various methods of machining for different processes which help to improve the productivity of the process are explored. A case study on machining of an aluminum manifold is done in which the existing process for machining is analyzed and various experiments are performed in order to find out the optimum cutting parameters and minimizing the cycle time of production of the manifold. The result helps to reduce the cycle time by a significant amount thereby reducing the total cost of production and increasing the production rate of the component with negligible capital investment.

Productivity improvement in manifold machining using CNC machines

2020 ◽  
pp. 79-94
Author(s):  
Rahul Aggarwal ◽  
Mehul Soni ◽  
Pranjal Singh ◽  
A. K. Madan
Keyword(s):  
Cycle Time ◽  
Capital Investment ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cnc Machining ◽  
Depth Of Cut ◽  
Productivity Improvement ◽  
Management Level ◽  
Set Up ◽  
Machining Productivity

This report focuses on the different methods to improve productivity at management level, at the machine shop and of machining methods. The various parameters effecting machining productivity i.e., cycle time, set-up time, idle time, operator skill level etc. including how CNC machining helps in optimizing these parameters are discussed and analysed in this paper. Effects of different cutting parameters like cutting speed, feed rate, depth of cut, effect of coolant etc. are also examined. Various methods of machining for different processes which help to improve the productivity of the process are explored. A case study on machining of an aluminium manifold is done in which the existing process for machining is analysed and various experiments are performed in order to find out the optimum cutting parameters and minimizing the cycle time of production of the manifold. The result helps to reduce the cycle time by a significant amount thereby reducing the total cost of production and increasing the production rate of the component with negligible capital investment.

scholarly journals Optimization with Taguchi Method of Influences on Surface Roughness of Cutting Parameters in CNC Turning Processing

Mechanika ◽  
2019 ◽  
Vol 25 (5) ◽  
pp. 397-405
Author(s):  
Mustafa özdemir
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Cnc Machine ◽  
Control Factors ◽  
Steel Material ◽  
Validation Tests

In this study, the effect of cutting speed, feed rate, and depth of cut on surface roughness was experimentally examined in the processing of AISI 409 (ferritic chromium stainless steel) material. As cutting parameters, three cutting speeds (200, 300, and 400 m/min), three feed rates (0.1, 0.2, and 0.3 mm/rev), and three depths of cut (1, 2 and 3 mm) were selected. Turning tests in CNC machine were made according to Taguchi L27 orthogonal array and the signal/noise (S/N) ratios were used in the evaluation of the experimental results. By using Taguchi method, cutting parameters giving the optimum surface roughness (Ra and Rz) values were determined. The effect of control factors on the results was found with the help of Analysis of Variance (ANOVA). According to ANOVA results, the most important parameters affecting the surface roughness were determined as feed rate, depth of cut, and cutting speed, respectively. By conducting validation tests, the optimization was observed to be applied successfully.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

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.

Manufacturability of Aircraft Winglet for Wind Tunnel Testing

2015 ◽  
Vol 830-831 ◽  
pp. 100-103
Author(s):  
L. Gopinath ◽  
S. Ravishankar
Keyword(s):  
Wind Tunnel ◽  
Metal Cutting ◽  
Tool Path ◽  
Cutting Parameters ◽  
Cnc Machining ◽  
Depth Of Cut ◽  
Manufacturing Strategy ◽  
Thin Sections ◽  
Good Surface ◽  
Good Surface Finish

The form, shape and dimensions of the scaled down winglet model become small and thin bringing complexity to manufacturing. The trailing edge tapers to a thickness varying from 0.065mm to 0.099mm along its length. The mounting portion of the winglet is provided with a close tolerance having a slot gap of 5mm and a depth of 35 mm with an angle. Additionally, wind tunnel models require good surface finish on the aerodynamic surfaces and this involves adopting a manufacturing strategy with a control over on the metal cutting parameters to be implemented on a three axes CNC machining centre. The winglet surface is divided into segments in order to handle the cutting forces on the varying aerodynamic cross section. Various metal cutting parameters such as tool path, cutter diameter, feed rate, depth of cut, spindle speed, etc., are evaluated by monitoring segments where the metal cutting is carried out [1] and flow of chips observed. Fixtures and lugs are planned effectively to accommodate the machining of the angular slot in a three axes machining centre itself. Routing of operations to handle the varying thin sections and realisation of the close tolerance slot has enabled a reliable manufacturing approach in an economical way.

OPTIMISING CUTTING PARAMETERS FOR HOT TURNING ON EN31 MATERIAL

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Prof. Hemant k. Baitule ◽  
Satish Rahangdale ◽  
Vaibhav Kamane ◽  
Saurabh Yende
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Multiple Time ◽  
Turning Process ◽  
Workpiece Material ◽  
Hot Turning

In any type of machining process the surface roughness plays an important role. In these the product is judge on the basis of their (surface roughness) surface finish. In machining process there are four main cutting parameter i.e. cutting speed, feed rate, depth of cut, spindle speed. For obtaining good surface finish, we can use the hot turning process. In hot turning process we heat the workpiece material and perform turning process multiple time and obtain the reading. The taguchi method is design to perform an experiment and L18 experiment were performed. The result is analyzed by using the analysis of variance (ANOVA) method. The result Obtain by this method may be useful for many other researchers.

Optimization of Cutting Parameters of Multiple Performance Characteristics in End Milling of AlSi/AIN MMC – Taguchi Method and Grey Relational Analysis

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
S. H. Tomadi ◽  
J. A. Ghani ◽  
C. H. Che Haron ◽  
M. S. Kasim ◽  
A. R. Daud
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Volume Fraction ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Relational Analysis ◽  
Grey Relational

The main objective of this paper is to investigate and optimize the cutting parameters on multiple performance characteristics in end milling of Aluminium Silicon alloy reinforced with Aluminium Nitride (AlSi/AlN MMC) using Taguchi method and Grey relational analysis (GRA). The fabrication of AlSi/AlN MMC was made via stir casting with various volume fraction of particles reinforcement (10%, 15% and 20%). End milling machining was done under dry cutting condition by using two types of cutting tool (uncoated & PVD TiAlN coated carbide). Eighteen experiments (L18) orthogonal array with five factors (type of tool, cutting speed, feed rate, depth of cut, and volume fraction of particles reinforcement) were implemented. The analysis of optimization using GRA concludes that the better results for the combination of lower surface roughness, longer tool life, lower cutting force and higher material removal could be achieved when using uncoated carbide with cutting speed 240m/min, feed 0.4mm/tooth, depth of cut 0.3mm and 15% volume fraction of AlN particles reinforcement. The study confirmed that with a minimum number of experiments, Taguchi method is capable to design the experiments and optimized the cutting parameters for these performance characteristics using GRA for this newly develop material under investigation.

Evaluation of Process Parameters in Machining of AA6063 Alloy

2018 ◽  
Vol 1148 ◽  
pp. 109-114
Author(s):  
M. Balaji ◽  
C.H. Nagaraju ◽  
V.U.S. Vara Prasad ◽  
R. Kalyani ◽  
B. Avinash
Keyword(s):  
Surface Roughness ◽  
Regression Analysis ◽  
Process Parameters ◽  
Single Channel ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Roughness Parameters ◽  
Surface Roughness Parameters ◽  
Aa6063 Alloy

The main aim of this work is to analyse the significance of cutting parameters on surface roughness and spindle vibrations while machining the AA6063 alloy. The turning experiments were carried out on a CNC lathe with a constant spindle speed of 1000rpm using carbide tool inserts coated with Tic. The cutting speed, feed rate and depth of cut are chosen as process parameters whose values are varied in between 73.51m/min to 94.24m/min, 0.02 to 0.04 mm/rev and 0.25 to 0.45 mm respectively. For each experiment, the surface roughness parameters and the amplitude plots have been noted for analysis. The output data include surface roughness parameters (Ra,Rq,Rz) measured using Talysurf and vibration parameter as vibration amplitude (mm/sec) at the front end of the spindle in transverse direction using single channel spectrum analyzer (FFT).With the collected data Regression analysis is also performed for finding the optimum parameters. The results show that significant variation of surface irregularities and vibration amplitudes were observed with cutting speed and feed. The optimum cutting speed and feed from the regression analysis were 77.0697m/min and 0.0253mm/rev. for the minimum output parameters. No significant effect of depth of cut on output parameters is identified.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

The Effects of Cutting Parameters on Work-Hardening of Milling Invar 36

2015 ◽  
Vol 1089 ◽  
pp. 373-376
Author(s):  
Xing Wei Zheng ◽  
Guo Fu Ying ◽  
Yan Chen ◽  
Yu Can Fu
Keyword(s):  
Work Hardening ◽  
Lattice Distortion ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Metallographic Structure ◽  
Metallographic Observation ◽  
Coated Carbide ◽  
Carbide Insert ◽  
Axial Depth

An experiment of face milling of Invar36 was conducted by using coated carbide insert, the microhardness was tested and the metallographic structure was observed to figure out the principles of work-hardening. The results showed that the depth of work-hardening ranges from 80μm to 160μm among the parameters selected in the experiments. The degree and the depth of work-hardening were significantly affected by the axial depth of cut and feed per tooth. The degree and the depth of work-hardening showed a tendency to increase with the increase of the axial depth of cut and feed per tooth. Compared with the axial depth of cut and feed per tooth, cutting speed had less influence on the degree and depth of work-hardening. The degree and depth of work- hardening decreased slowly with the increase of cutting speed. Metallographic observation showed that work-hardening layer consisted of the thermal force influenced layer and the force influenced layer, while the amorphous metallographic structure was observed in the thermal force influenced layer, and lattice distortion was observed in the force influenced layer.

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