scholarly journals Investigating the impact of chucks on the stability of a milling process

2021 ◽  
Vol 25 (5) ◽  
pp. 549-558
Author(s):  
A. S. Pyatykh ◽  
P. P. Shaparev
Keyword(s):  
Dynamic Stability ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Milling Process ◽  
Numerical Control ◽  
End Mill ◽  
Solid Carbide ◽  
The Impact ◽  
Power Chuck

The impact of a tool chuck on the dynamic stability of a milling process with an end mill was investigated using a workpiece made of aluminium wrought alloy V95pchT2. To assess the dynamic stability, we analysed a Fourier transformed signal recorded during milling using a Shure PGA81 -XLR tool directional microphone. The milling was performed on an HSC75 linear high-production machining centre with an H10F solid carbide end mill. Cutting conditions were calculated based on a stability diagram derived from an operational modal analysis of a manufacturing system. The surface roughness was measured with a Taylor Hobson Form Talysurf i200 contact profilometer. Performance defined by the rate of material removal and the roughness of a treated surface was used to evaluate the cutting process. A correlation was found between the type of tool chuck fixating the end mill, the rate of material removal and the roughness of the machined surface. It was found that, for milling using a power chuck, the areas of stable cutting correspond to the max imum cutting depth equal to 5.6 mm at a cutting width of 16 mm and a cutting feed of 0.1 mm/rev. However, for the other studied chucks, this indicator was 20 to 30% lower. End milling conducted using a power chuck with a solid carbide cutter with a diameter of 16 mm and three cutting teeth resulted in dynamically stable cutting with the highest material removal rate (575.6 cm3/min) and minimum surface roughnes s (0.56 μm). Based on the conducted analysis, for the operation of end milling on a machine with computerised numerical control (CNC), a power tool chuck is recommended that improves milling performance by over 25% relative to the considered tool setups. Furthermore, this preserves the quality of a treated surface and increases the tool cutting life owing to dynamically stable cutting.

A Model to Determine the Effect of Tool Diameter on the Critical Feed Rate for Ductile-Brittle Transition in Milling Process of Brittle Material

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
Muhammad Arif ◽  
Mustafizur Rahman ◽  
Wong Yoke San
Keyword(s):  
Brittle Material ◽  
Material Removal ◽  
Removal Rate ◽  
Milling Process ◽  
Experimental Results ◽  
End Mill ◽  
Brittle Transition ◽  
Proposed Model ◽  
Ductile Mode ◽  
Tool Diameter

This paper presents analytical and experimental results of ductile-mode machining of brittle material by milling process. In milling process of brittle material, feed per edge is the predominant parameter to achieve ductile-mode machining and hence it limits the permissible material removal rate. An analytical model has been proposed to evaluate the effect of tool diameter on the critical feed per edge for ductile-brittle transition in milling process of brittle material. The proposed model has been validated experimentally by performing microcutting tests on tungsten carbide workpiece by milling process. It has been established by the model and the experimental results that an end-mill of larger diameter improves the critical feed per edge for ductile-brittle transition in milling process of brittle material.

Optimization of Tool Wear, Surface Roughness and Material Removal Rate in the Milling Process of Al 6061 Using Taguchi and Weighted Principal Component Analysis (WPCA)

2014 ◽  
Vol 493 ◽  
pp. 535-540 ◽  
Author(s):  
Laily Ulfiyah ◽  
Bambang Pramujati ◽  
Bobby Oedy Pramoedyo Soepangkat
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Principal Component ◽  
Milling Process ◽  
Performance Characteristics ◽  
Weighted Principal Component ◽  
End Milling Process

In the metal cutting industry, end milling has an important role in cutting metal to obtain the various required shapes and size. This study takes Al 6061 as working material and investigates three performance characteristics, i.e., tool wear (VB), surface roughness (Ra) and material removal rate (MRR), with Taguchi method and WPCA for determining the optimal parameters in the end milling process. The performance characteristic of MRR is larger-the-better while VB and Ra are having smaller-the-better performance characteristic. Based on Taguchi method, an L18 mixed-orthogonal array was chosen for the experiments. The optimization was conducted by using weighted principal component analysis (WPCA). As a result, the optimization of complicated multiple performance characteristics was transformed into the optimization of single response performance index. The most significant machining parameters which affected the multiple performance characteristics were type of milling operation, spindle speed, feed rate and depth of cut. Experimental result have also shown that machining performance characteristics of end milling process can improved effectively through the combination of Taguchi method and WPCA.

A Metric for Defining the Energy Efficiency of Thermally-Assisted Machining

2006 ◽  
Author(s):  
Frank Pfefferkorn ◽  
Shuting Lei
Keyword(s):  
Energy Efficiency ◽  
Silicon Nitride ◽  
Thermal Energy ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Operating Conditions ◽  
The Body ◽  
Machining Processes ◽  
The Impact

A significant amount of work has been conducted on thermally-assisted machining with a great deal being focused on laser-assisted machining. The body of work has shown that preheating of the workpiece (usually localized heating) makes it possible to machine certain structural ceramics with a conventional cutting tool, improves the machinability of superalloys, and improves the micro-end milling of metals. A variety of metrics have been used to ascertain the impact of thermal assistance on the machining of these materials including: specific cutting energy, tool wear rate, surface roughness, residual stress, material removal rate, material removal mechanism, cost, and surface integrity. Combined, these quantities provide a good but incomplete description of the process and efficacy of thermal assistance. This manuscript looks at the flow of energy in thermally-assisted machining in an attempt to determine how beneficial preheating is. Some efficiency metrics are suggested and used to study the data that has been collected to date. The total thermal energy deposited in the workpiece is compared to the theoretical minimum required to heat the removed material in order to determine what percentage of the deposited (i.e. absorbed) energy is actually used in assisting the cutting process. This enables a comparison between cutting processes (e.g. end milling and turning) and operating conditions to determine how efficiently the added thermal energy is being used. Compared with other machinability metrics the thermal energy efficiency is used to evaluate how beneficial preheating is to the machining processes studied. Two sets of data are studied: laser-assisted turning of silicon nitride and partially-stabilized zirconia. The specific energy for LAM of silicon nitride is compared to that for grinding of silicon nitride. It is hoped that this presentation will spark debate in the manufacturing community and provide more insight into thermally-assisted manufacturing.

Tool Path Planning for Near-Dry EDM Milling With Lead Angle on Curved Surfaces

2011 ◽  
Vol 133 (5) ◽  
Author(s):  
Masahiro Fujiki ◽  
Jun Ni ◽  
Albert J. Shih
Keyword(s):  
Path Planning ◽  
Material Removal Rate ◽  
Material Removal ◽  
Tool Path ◽  
End Milling ◽  
Removal Rate ◽  
Milling Process ◽  
Tool Path Planning ◽  
Lead Angle ◽  
Tubular Electrode

This research investigates the strategy to achieve high material removal rate in tool path planning for the near-dry electrical discharge machining (EDM) milling process using tubular electrode with a lead angle. The proposed strategy to prevent leakage of dielectric mist from the tubular electrode is different from the conventional end milling process due to the difference in material removal mechanism. Tool positions and orientations to engage the electrode into workpiece, machining of workpiece edge, minimum lead angle to machine a curved surface, and minimum and maximum path interval to prevent the mist leakage are derived. Experiments are conducted to validate the model prediction of path planning. Experimental results show plunge method has the highest material removal rate for engaging method, and electrode hole must be located within the workpiece surface when edge of workpiece is machined. For curvature machining, the proposed path planning strategy yields higher material removal rate compared with that from the conventional strategy, which only avoids gouging. This study also reveals that, due to the tool wear and crowning of electrode tip, it is difficult to accurately determine the minimum path interval which will cause the mist leakage.

scholarly journals A surrogate-assisted optimization approach for multi-response end milling of aluminum alloy AA3105

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2419-2439
Author(s):  
Tamal Ghosh ◽  
Yi Wang ◽  
Kristian Martinsen ◽  
Kesheng Wang
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Data Driven ◽  
Optimal Cutting Parameters

Abstract Optimization of the end milling process is a combinatorial task due to the involvement of a large number of process variables and performance characteristics. Process-specific numerical models or mathematical functions are required for the evaluation of parametric combinations in order to improve the quality of the machined parts and machining time. This problem could be categorized as the offline data-driven optimization problem. For such problems, the surrogate or predictive models are useful, which could be employed to approximate the objective functions for the optimization algorithms. This paper presents a data-driven surrogate-assisted optimizer to model the end mill cutting of aluminum alloy on a desktop milling machine. To facilitate that, material removal rate (MRR), surface roughness (Ra), and cutting forces are considered as the functions of tool diameter, spindle speed, feed rate, and depth of cut. The principal methodology is developed using a Bayesian regularized neural network (surrogate) and a beetle antennae search algorithm (optimizer) to perform the process optimization. The relationships among the process responses are studied using Kohonen’s self-organizing map. The proposed methodology is successfully compared with three different optimization techniques and shown to outperform them with improvements of 40.98% for MRR and 10.56% for Ra. The proposed surrogate-assisted optimization method is prompt and efficient in handling the offline machining data. Finally, the validation has been done using the experimental end milling cutting carried out on aluminum alloy to measure the surface roughness, material removal rate, and cutting forces using dynamometer for the optimal cutting parameters on desktop milling center. From the estimated surface roughness value of 0.4651 μm, the optimal cutting parameters have given a maximum material removal rate of 44.027 mm3/s with less amplitude of cutting force on the workpiece. The obtained test results show that more optimal surface quality and material removal can be achieved with the optimal set of parameters.

Process Design and Optimization of end Milling Parameters of Al 7075 Metal Matrix Composite

2021 ◽  
pp. 929-937
Author(s):  
D. S. Sai Ravi Kiran ◽  
Alavilli Sai Apparao ◽  
Vempala GowriSankar ◽  
Shaik Faheem ◽  
Sheik Abdul Mateen ◽  
...  
Keyword(s):  
Tool Wear ◽  
Material Removal Rate ◽  
Metal Matrix ◽  
Material Removal ◽  
Hybrid Composites ◽  
End Milling ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Weight Percentage

This paper investigates the machinability characteristics of end milling operation to yield minimum tool wear with the maximum material removal rate using RSM. Twenty-seven experimental runs based on Box-Behnken Design of Response Surface Methodology (RSM) were performed by varying the parameters of spindle speed, feed and depth of cut in different weight percentage of reinforcements such as Silicon Carbide (SiC-5%, 10%,15%) and Alumina (Al2O3-5%) in alluminium 7075 metal matrix. Grey relational analysis was used to solve the multi-response optimization problem by changing the weightages for different responses as per the process requirements of quality or productivity. Optimal parameter settings obtained were verified through confirmatory experiments. Analysis of variance was performed to obtain the contribution of each parameter on the machinability characteristics. The result shows that spindle speed and weight percentage of SiC are the most significant factors which affect the machinability characteristics of hybrid composites. An appropriate selection of the input parameters such as spindle speed of 1000 rpm, feed of 0.02 mm/rev, depth of cut of 1 mm and 5% of SiC produce best tool wear outcome and a spindle speed of 1838 rpm, feed of 0.04 mm/rev, depth of cut of 1.81 mm and 6.81 % of SiC for material removal rate.

Investigation of Surface Roughness and Material Removal Rate for High Speed Micro End Milling on PMMA

2015 ◽  
Vol 1115 ◽  
pp. 12-15
Author(s):  
Nur Atiqah ◽  
Mohammad Yeakub Ali ◽  
Abdul Rahman Mohamed ◽  
Md. Sazzad Hossein Chowdhury
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Micro End Milling

Micro end milling is one of the most important micromachining process and widely used for producing miniaturized components with high accuracy and surface finish. This paper present the influence of three micro end milling process parameters; spindle speed, feed rate, and depth of cut on surface roughness (Ra) and material removal rate (MRR). The machining was performed using multi-process micro machine tools (DT-110 Mikrotools Inc., Singapore) with poly methyl methacrylate (PMMA) as the workpiece and tungsten carbide as its tool. To develop the mathematical model for the responses in high speed micro end milling machining, Taguchi design has been used to design the experiment by using the orthogonal array of three levels L18 (21×37). The developed models were used for multiple response optimizations by desirability function approach to obtain minimum Ra and maximum MRR. The optimized values of Ra and MRR were 128.24 nm, and 0.0463 mg/min, respectively obtained at spindle speed of 30000 rpm, feed rate of 2.65 mm/min, and depth of cut of 40 μm. The analysis of variance revealed that spindle speeds are the most influential parameters on Ra. The optimization of MRR is mostly influence by feed rate. Keywords:Micromilling,surfaceroughness,MRR,PMMA

Modeling of Material Removal Mechanism in Micro Electric Discharge Milling of Ti-6Al-4V

2014 ◽  
Vol 592-594 ◽  
pp. 516-520 ◽  
Author(s):  
Basil Kuriachen ◽  
Jose Mathew
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Milling Process ◽  
Work Piece ◽  
Machining Parameters ◽  
Removal Mechanism ◽  
Material Removal Mechanism ◽  
Electric Discharge Milling

Micro EDM milling process is accruing a lot of importance in micro fabrication of difficult to machine materials. Any complex shape can be generated with the help of the controlled cylindrical tool in the pre determined path. Due to the complex material removal mechanism on the tool and the work piece, a detailed parametric study is required. In this study, the influence of various process parameters on material removal mechanism is investigated. Experiments were planned as per Response Surface Methodology (RSM) – Box Behnken design and performed under different cutting conditions of gap voltage, capacitance, electrode rotation speed and feed rate. Analysis of variance (ANOVA) was employed to identify the level of importance of machining parameters on the material removal rate. Maximum material removal rate was obtained at Voltage (115V), Capacitance (0.4μF), Electrode rotational Speed (1000rpm), and Feed rate (18mm/min). In addition, a mathematical model is created to predict the material removal

Modelling and Optimization of End Milling Process Using TLBO and TOPSIS Algorithm

2017 ◽  
pp. 54-81 ◽  
Author(s):  
Atul Tiwari ◽  
Mohan Kumar Pradhan
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Metal Cutting ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Depth Of Cut ◽  
Multi Objective ◽  
Order Preference

To assure desire quality of machined products at minimum machining costs and maximum material removal rate, it is very important to select optimum parameters when metal cutting machine tool are used. Minimum Surface Roughness (Ra) is commonly desirable for the component; however Material Removal Rate (MRR) should be maximized. This chapter presents an approach for determination of the best cutting parameters precede to minimum Ra and maximum MRR simultaneously by integrating Response Surface Methodology with Multi-Objective Technique for Order Preference by Similarity to Ideal Solution and Teaching and learning based optimization algorithm in face milling of Al-6061 alloy. 30 experiments have been conducted based on RSM with 4 parameters, namely Speed, Feed, Depth of Cut and Coolant Speed and three levels each. ANOVA is performed to find the most influential input parameters for both MRR and Ra. Later the multi-objective attribution selection method TOPSIS and multi objective optimization method TLBO is used to optimize the responses.

Sign in / Sign up

Export Citation Format

Share Document