Experimental Study on Milling Parameters Regression and Optimization of Super High Strength Steel 30CrMnSiNi2A

2012 ◽  
Vol 723 ◽  
pp. 293-298 ◽  
Author(s):  
Ming Chen ◽  
Cheng Dong Wang ◽  
Li Jiang ◽  
Qiu Lin Niu
Keyword(s):  
Surface Roughness ◽  
Regression Model ◽  
Cutting Force ◽  
High Strength Steel ◽  
Metal Removal ◽  
Removal Rate ◽  
Multiple Linear Regression Model ◽  
High Strength ◽  
Parameters Optimization ◽  
Milling Parameters

In this paper, effects of milling parameters on cutting force and surface roughness during symmetrical face dry milling process of super high strength steel 30CrMnSiNi2A were presented. Multiple linear regression model and orthogonal rotary quadratic regression model were established to analyze cutting force and surface roughness, respectively. Their adequacy was estimated by variance analysis and experimental data comparison. Parameters optimization for maximum metal removal rate and minimum surface roughness were also discussed.

Cutting force, tool wear and surface roughness in high-speed milling of high-strength steel with coated tools

2019 ◽  
Vol 33 (11) ◽  
pp. 5393-5398 ◽  
Author(s):  
Yuan Li ◽  
Guangming Zheng ◽  
Xu Zhang ◽  
Xiang Cheng ◽  
Xianhai Yang ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Cutting Force ◽  
High Strength Steel ◽  
High Speed ◽  
High Strength ◽  
High Speed Milling ◽  
Coated Tools

scholarly journals Prediction Model of Cutting Parameters for Turning High Strength Steel Grade-H: Comparative Study of Regression Model versus ANFIS

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Adel T. Abbas ◽  
Mohanad Alata ◽  
Adham E. Ragab ◽  
Magdy M. El Rayes ◽  
Ehab A. El Danaf
Keyword(s):  
Experimental Data ◽  
Surface Roughness ◽  
Regression Analysis ◽  
High Strength Steel ◽  
Removal Rate ◽  
High Strength ◽  
Cutting Parameters ◽  
Turning Operations ◽  
Cnc Turning ◽  
Accuracy And Repeatability

The Grade-H high strength steel is used in the manufacturing of many civilian and military products. The procedures of manufacturing these parts have several turning operations. The key factors for the manufacturing of these parts are the accuracy, surface roughness (Ra), and material removal rate (MRR). The production line of these parts contains many CNC turning machines to get good accuracy and repeatability. The manufacturing engineer should fulfill the required surface roughness value according to the design drawing from first trail (otherwise these parts will be rejected) as well as keeping his eye on maximum metal removal rate. The rejection of these parts at any processing stage will represent huge problems to any factory because the processing and raw material of these parts are very expensive. In this paper the artificial neural network was used for predicting the surface roughness for different cutting parameters in CNC turning operations. These parameters were investigated to get the minimum surface roughness. In addition, a mathematical model for surface roughness was obtained from the experimental data using a regression analysis method. The experimental data are then compared with both the regression analysis results and ANFIS (Adaptive Network-based Fuzzy Inference System) estimations.

Experimental Study on Cryogenic Cutting of High-Strength Steel with Liquid Nitrogen Cooling

2011 ◽  
Vol 328-330 ◽  
pp. 470-473 ◽  
Author(s):  
Shu Juan Li ◽  
Yong Ke Hu ◽  
Xue Jiang ◽  
Juan Du
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
High Strength Steel ◽  
Cutting Speed ◽  
High Strength ◽  
Dry Cutting ◽  
Chip Breaking ◽  
Cryogenic Cutting ◽  
Hard Cutting ◽  
Made In

As a modern manufacturing technology, cryogenic cutting technology is one of effective ways to improve machining efficiency of hard-cutting materials.With typical hard-cutting materials 35CrMnSiA and 45CrNiMoV high-strength steel as the research object, the comparison experiment between cryogenic cutting and dry cutting of two kinds of high-strength steels was made in this paper. In the changing cutting speed conditions, the cutting force and the surface roughness of two kinds of cutting were measured in this experiment.By changing the length of cutting stroke, the cutter wear of two kinds of cutting was measured, and a comparison of chip-breaking effects was made in the experiment.The experimental results indicate that the cutting force, surface roughness, and tool wear in cutting 35CrMnSiA and 45CrNiMoV high-strength steel under cryogenic condition are reduced, and chip-breaking effect of cryogenic cutting is improved. This may be attributed mainly to improve the machinability of higth-strength steel.

scholarly journals Surface Grinding Parameters Optimization of Austenitic Stainless Steel (AISI 304)

2020 ◽  
pp. 511-515
Author(s):  
Tushar Khule ◽  
Rahul Naravade ◽  
Sagar Shelke
Keyword(s):  
Surface Roughness ◽  
Large Scale ◽  
Metal Removal ◽  
Removal Rate ◽  
Parameters Optimization ◽  
Surface Grinding ◽  
Machining Process ◽  
Project Work ◽  
Depth Of Cut ◽  
Set Up

The assembling procedure of surface grinding has been set up in the large scale manufacturing of thin, rotationally even parts. Due to the complex set-up and geometrical, kinematical, dynamical influence parameters, surface grinding is rarely applied within limited-lot production. Surface crushing is a basic procedure for last machining of parts requiring smooth surfaces and exact resiliences.As contrasted and other machining forms, crushing is exorbitant activity that ought to be used under ideal conditions.. Although widely used in industry. The project work takes the following input processes parameters namely Work speed, feed rate and depth of cut. The main objective of this work is to predict the grinding behaviour and achieve optimal operating processes parameters. A software package is utilized which integrates these various models to simulate what happens during surface grinding processes. Predictions from this simulation will be further analysed by calibration with actual data. The main objective in any machining process is to maximize the Metal Removal Rate (MRR) and to minimize the surface roughness (Ra). In order to optimize these values Taguchi method, ANOVA is used. The surface roughness (Ra) value and Material Removal Rate (MRR), obtained from experimentation and confirmation test, for this the optimum control parameters are analysed.

Study on Milling Parameters Optimization in Remanufacturing Cold-Welding Area

2012 ◽  
Vol 500 ◽  
pp. 123-127 ◽  
Author(s):  
Qing Zhong Xu ◽  
Fang Yi Li ◽  
Shi Lei Ma ◽  
Jun Zhuang Liu
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
High Efficiency ◽  
Regression Method ◽  
Parameters Optimization ◽  
Linear Regression Method ◽  
Cold Welding ◽  
Range Analysis ◽  
Milling Force ◽  
Milling Parameters

Considering cold-welding repaired layer is rough and microstructure contains hard phases, firstly, the two-factor three-level orthogonal milling experiment was conducted in remanufacturing cold-welding repaired area, then the influences of different parameters on Ni-base cold-welding repaired layer milling were studied. At the end, cutting force and surface roughness were used as objectives to optimize the milling parameters. Cutting force and surface roughness were processed by range analysis, and their influence sequences were obtained. The empirical formula of milling force and surface roughness can be obtained through linear regression method, which provided theoretical base for the prediction. The influences on cutting force and surface roughness of different parameters were studied to further optimization, which can provide technical support for high efficiency and precision cutting in cold-welding area.

Research on Deep-hole Drilling Quality of High-strength Steel With Slender Gun Drill

2021 ◽  
Author(s):  
Jiabin Liang ◽  
Li Jiao ◽  
Pei Yan ◽  
Minghui Cheng ◽  
Tianyang Qiu ◽  
...  
Keyword(s):  
Cutting Force ◽  
High Strength Steel ◽  
Fluid Pressure ◽  
Cutting Speed ◽  
High Strength ◽  
Feed Speed ◽  
Machining Parameters ◽  
Deep Hole ◽  
Machining Quality ◽  
Gun Drill

Abstract There are a lot of problems exist in the processing of long and thin deep hole gun drilling of high strength steel, such as insufficient of the machining mechanism and characteristics of gun drilling, difficulty in selecting machining parameters, unknown influence mechanism of machining parameters on drilling force, drilling temperature and machining quality. In this paper, 42CrMo high strength steel is selected as the workpiece material. A numerical model of cutting force is established based on the mechanism of gun drill, and then the finite element simulation and processing test are carried out. The results show that the cutting force decreases with the increase of cutting speed, and increases with the increase of feed speed; the error between the theoretical and actual value is less than 10%. Cutting speed and feed speed have a great influence on machining quality, and the cutting fluid pressure mainly affects the surface roughness.

scholarly journals Optimization of Milling Parameters of Unmodified Calotropis Procera Fiber-Reinforced PLA Composite (UCPFRPC)

2021 ◽  
Vol 5 (10) ◽  
pp. 261
Author(s):  
Hassan K. Langat ◽  
Fredrick M. Mwema ◽  
James N. Keraita ◽  
Esther T. Akinlabi ◽  
Job M. Wambua ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Removal Rate ◽  
Infrared Camera ◽  
Calotropis Procera ◽  
Depth Of Cut ◽  
Fiber Reinforced ◽  
Machining Time ◽  
Milling Parameters ◽  
Milling Temperature

This study involves the optimization of the milling parameters of unmodified Calotropis Procera fiber-reinforced PLA composite (UCPFRPC). The material is prepared from the combination of 20% Calotropis-Procera and 80% of PLA by weight. The experiments are designed using the Taguchi methodology, where 16 experiments are obtained using the spindle rotational speed, depth of cut, and feed rate as the parameters. These experiments were conducted while obtaining thermal images using an infrared camera and recording the machining time. The change in mass was then determined and the material removal rate computed. The machined workpieces were then investigated for surface roughness. The study shows that the optimal milling parameters in the machining of UCPFRPC for the lowest surface roughness are 400 rpm, 400 mm/min, and 0.2 mm, for the rotational spindle speed, feed rate, and depth of cut. The parameters were 400 rpm, 100 mm/min, and 1.2 mm for the largest MRR, and 400 rpm, 400 mm/min, and 0.2 mm for the least average milling temperature. In all the responses, the depth of cut is the most significant factor.

Effects of Cutting Parameters on the Surface Roughness of Ti6Al4V Titanium Alloys in Side Milling

2011 ◽  
Vol 175 ◽  
pp. 289-293 ◽  
Author(s):  
Hao Liu ◽  
Chong Hu Wu ◽  
Rong De Chen
Keyword(s):  
Surface Roughness ◽  
Titanium Alloys ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Cutting Depth ◽  
Side Milling ◽  
Milling Parameters ◽  
Fine Grain

Side milling Ti6Al4V titanium alloys with fine grain carbide cutters is carried out. The influences of milling parameters on surface roughness are investigated and also discussed with average cutting thickness, material removal rate and vibration. The results reveal that the surface roughness increases with the increase of average cutting thickness and is primarily governed by the radial cutting depth.

Optimization of MRR and Surface Roughness of AlMg3 (AA5754) Alloy in CNC Lathe Machine by Using Taguchi Method

2018 ◽  
Vol 877 ◽  
pp. 110-117 ◽  
Author(s):  
Poornesh Kumar Chaturvedi ◽  
Harendra Kumar Narang ◽  
Atul Kumar Sahu
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Metal Removal ◽  
Removal Rate ◽  
Surface Condition ◽  
Point Of View ◽  
Depth Of Cut ◽  
Metal Removal Rate ◽  
Cnc Lathe ◽  
Lathe Machine

Quality of the product is the major concern in manufacturing industries from customers as well as producers point of view. There are number of factors in the product such as surface condition, height, weight, length, width etc., which may be consider for the measurement of the quality. Surface roughness and Metal Removal Rate (MRR) are the two main outcomes on which numerous researchers have applied different approaches for several years to get optimum results. In this study, Taguchi Method is applied for getting optimum parameters settings for Surface roughness and Metal Removal Rate (MRR) in case of turning AlMg3 (AA5754) in CNC Lathe machine, which is an aluminum alloy having diameter 20 mm and length 100 mm. The three parameters i.e. spindle speed, feed rate and depth of cut with 3 levels are taken as the process variables and the working ranges of these parameters for conducting experiments are selected based on Taguchi’s L9 Orthogonal Array (OA) design. To analyze the significant process parameters; main effect plots for data means and for S/N ratio are generated using Minitab statistical software.

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