Effect Of Tool Geometry Parameters Research Articles

Effects of Tool Geometry Parameters on Clinched Joint Strength Using FEM

Abstract Clinching joining is one of the predominant techniques used to join aluminium alloys in the automotive industry. Although the technique can be easily automated, cost-effective, and not affect the material’s mechanical properties during the joining process, the tool geometry parameters significantly affect the strength of the clinched joint. Therefore, a precise finite element model is critical to improve the strength and reduce the cliched joint’s production cost. This study investigated the effect of the punch fillet radius, the punch angle, the die diameter and the die depth on the strength of the clinched joint of 5754 aluminium alloys. The clinched joint was produced with different geometry parameters. The cross-section of the clinched joints was observed. In the meantime, the interlocking value, the neck thickness, and tool parameters were measured to investigate the joinability of the aluminium alloys. The static tensile shear tests were also conducted using the universal tensile machine. Numerical studies have been conducted to analyse the influence of the geometrical parameters using a 2D axisymmetric model. As a result, the numerical results agreed with the experimental results. Additionally, the result showed that the tool geometry significantly impacted the strength of the clinched joint of aluminium alloys. The study concluded that the neck thickness and the interlocking value have played a vital role in the enhancement of the cliched joint strength.

Investigation of machining quality indicators and effect of tool geometry parameters during the machining of difficult-to-machine metal

Producing high-quality surfaces from hard and brittle metals presents a formidable challenge that calls for a meticulous machining strategy and an effective cutting tool. The mechanism of tool failure, chip formation behavior, and micro-morphology of the machined surface are crucial factors in determining a correlation between the used parameters and the machined surface quality. Among the metrics employed to assess the effectiveness of the tool. However, the determination of optimum machining parameters requires the repetition of precise experimental investigations with every change in the cutting conditions. The current research work proposes a set of suggestions for choosing the optimal tool parameters based on the micro-morphological characteristics of the tool and the machining performance indicators. A WC-Co ball end mill tool was used for the machining of an H13 tool steel workpiece to establish the relationship between changes in tool geometrical parameters and the machining performance indicators. Tool geometry with a rake angle of 3°, a clearance angle of 10°, and a helix angle of 32° was found to have the least wear band length at 56 μm. Moreover, the impact of tool geometry on the quality of the surface produced through machining was also investigated.

Effect of Tool Geometry Parameters on the Formability of a Camera Cover in the Deep Drawing Process.

The formability of the drawn part in the deep drawing process depends not only on the material properties, but also on the equipment used, metal flow control and tool parameters. The most common defects can be the thickening, stretching and splitting. However, the optimization of tools including the die and punch parameters leads to a reduction of the defects and improves the quality of the products. In this paper, the formability of the camera cover by aluminum alloy A1050 in the deep drawing process was examined relating to the tool geometry parameters based on numerical and experimental analyses. The results showed that the thickness was the smallest and the stress was the highest at one of the bottom corners where the biaxial stretching was the predominant mode of deformation. The problems of the thickening at the flange area, the stretching at the side wall and the splitting at the bottom corners could be prevented when the tool parameters were optimized that related to the thickness and stress. It was clear that the optimal thickness distribution of the camera cover was obtained by the design of tools with the best values—with the die edge radius 10 times, the pocket radius on the bottom of the die 5 times, and the punch nose radius 2.5 times the sheet thickness. Additionally, the quality of the camera cover was improved with a maximum thinning of 25% experimentally, and it was within the suggested maximum allowable thickness reduction of 45% for various industrial applications after optimizing the tool geometry parameters in the deep drawing process.

Tool determination and geometry parameter optimization of carbide tool in high-speed milling of third-generation γ-TiAl alloy

Gamma titanium aluminide alloys (γ-TiAl) are widely recognized as potential replacement for nickel-based superalloys in aerospace. However, along with brittleness at room temperature, poor surface quality and sever tool wear undermine their machinability, so that γ-TiAl alloy is considered as a typical intractable material. Tool selection and geometry optimization are encouraging strategies to improve the machinability of this kind of material. In this work, the cutting performance of six carbide grade tools is compared. And the cutting force, surface roughness and tool wear are selected as the evaluation criterion for the tool material determination. Then, the effects of tool geometry parameters including rake angle, primary relief angle and helix angle on surface roughness and tool wear are further studied. The sample dataset is utilized to formulate the first-order model with interaction. The predicted results of these models accorded well with the measured results. Due to the multi-performance characteristics, grey relational analysis method is introduced into the optimization of tool geometry parameters. The analysis of variance is employed to identify the most significant factor. And then, the confirmation test showed the improvement of the multi-performance characteristics.

A framework for simulation-based multi-objective optimization and knowledge discovery of machining process

The current study presents an effective framework for automated multi-objective optimization (MOO) of machining processes by using finite element (FE) simulations. The framework is demonstrated by optimizing a metal cutting process in turning AISI-1045, using an uncoated K10 tungsten carbide tool. The aim of the MOO is to minimize tool-chip interface temperature and tool wear depth, that are extracted from FE simulations, while maximizing the material removal rate. The effect of tool geometry parameters, i.e., clearance angle, rake angle, and cutting edge radius, and process parameters, i.e., cutting speed and feed rate on the objective functions are explored. Strength Pareto Evolutionary Algorithm (SPEA2) is adopted for the study. The framework integrates and connects several modules to completely automate the entire MOO process. The capability of performing the MOO in parallel is also enabled by adopting the framework. Basically, automation and parallel computing, accounts for the practicality of MOO by using FE simulations. The trade-off solutions obtained by MOO are presented. A knowledge discovery study is carried out on the trade-off solutions. The non-dominated solutions are analyzed using a recently proposed data mining technique to gain a deeper understanding of the turning process.

Investigation of Effects of Tool Geometry Parameters on Cutting Forces, Temperature and Tool Wear in Turning Using Finite Element Method and Taguchi’s Technique

Turning is one of the most widely metal cutting methods. Machines, tool geometry and machining parameters are the main factors influencing machining quality and efficiency. So there is a lot of research on it. This paper studies on the influence of the geometrical parameters of the tool including: back rake angle (BR), side rake angle (SR) and side cutting-edge angle (SCEA) on cutting forces, temperature and tool wear in turning using FEM (by Deform 3D finite element simulation software) and Taguchi’s technique (by Minitab16 statistical software) is used to design the experiment and to analyze output quality characteristics from simulation results. And the optimum tool geometry parameters are given.

Effect of Cutting Tool Geometry on Morphology of flank Wear Land in Turning of Low Carbon Steels

The amount of flank wear is often used as the criterion for tool life assessment because it influences work material surface roughness and accuracy. In this study, the influence of cutting tool geometry (angles) on morphology of flank wear land during turning of low carbon steel is investigated by using image processing techniques and Response Surface Methodology (RSM). The analysis was based on a second order model in which the flank wear (area and shape factors) is expressed as a function of three cutting tool geometry parameters (relief angle, rake angle and cutting edge angle) and the effect of tool geometry parameters and their interactive effect on flank wear land morphology have been investigated. It is found that the area and shape factors of flank wear land are highly affected by the cutting tool geometry parameters considered in the present study.

Optimization of tool geometry parameters for turning operations based on the response surface methodology

This investigation focuses on the influence of tool geometry on the surface finish obtained in turning of AISI 1040 steel. In order to find out the effect of tool geometry parameters on the surface roughness during turning, response surface methodology (RSM) was used and a prediction model was developed related to average surface roughness (Ra) using experimental data. The results indicated that the tool nose radius was the dominant factor on the surface roughness. In addition, a good agreement between the predicted and measured surface roughness was observed. Therefore, the developed model can be effectively used to predict the surface roughness on the machining of AISI 1040 steel with in 95% confidence intervals ranges of parameters studied.