Seyed Ali Niknam

Factors governing burr formation during high-speed slot milling of wrought aluminum alloys

Burr formation and edge finishing are research topics with high relevance to industrial applications. To remove burrs, however, a secondary operation known as deburring is usually required. Deburring is more complex and costly when dealing with milled parts, because multiple burrs form at different locations with various sizes. Therefore, proper selection of process parameters to minimize the burr size is strongly recommended. Therefore, this requires an understanding of milling burr formation mechanism and the governing cutting parameters on milling burrs. In this article, a multilevel experimental study is arranged to investigate the effects of machining conditions, tooling and workpiece materials on burr size (height and thickness). Statistical tools are then used to determine the dominant cutting parameters on burr size and to effectively prescribe an operational window to control and minimize burr formation. It was found that optimum setting levels of process parameters to minimize each burr are different. The analysis of results shows the significant effects of cutting tool, feed per tooth and depth of cut on slot milling burrs.

Machinability and Machining of Titanium Alloys: A Review

This chapter reviews the main difficulties impairing the machinability of titanium alloys. The overview of machinability of titanium alloys is presented with respect to the following performance criteria: cutting tool wear/tool life, cutting forces, chip formation, and surface integrity attributes, mainly surface roughness. Thereafter, the effects of various lubrication and cooling methods in machining titanium alloys is also discussed. Furthermore, a case study on the metallic particle emission when machining Ti-6A1-4V is also presented.

Milling burr formation, modeling and control: A review

Because of global competition, manufacturing industries today must provide high-quality products on time to remain competitive. High-quality mechanical parts include those with better surface finish and texture, dimension and form accuracies, reduced residual stress and burr-free. Burr formation is one of the most common and undesirable phenomenon occurring in machining operations, which reduces assembly and machined part quality. To remove burrs, a secondary operation known as deburring is required for post-processing and edge finishing operations. Since deburring is costly and considered a non-value-added process, the goal is desired to eliminate burrs or reduce the effort required to remove them. Because of non-uniform chip thickness, tool runout and complex interactive effects between cutting process parameters, milling burr formation is a very complex mechanism. Therefore, research and close attention are still needed in order to minimize and control milling burr formation. In this article, a review of burr formation and characterization is presented, along with burr formation modeling and control. An overview of factors governing milling burr formation is also presented.

Analysys and Optimization of Exit Burr Size and Surface Roughness in Milling Using Desireability Function

The burr formation mechanism and surface quality highly depend on machining conditions. Improper selection of cutting parameters may cause tremendous manufacturing cost and low product quality. Proper selection of cutting parameters which simultaneously minimize burr size and surface roughness is therefore very important, as that would reduce the part finishing cost. This article aims to present an experimental study to evaluate parameters affecting the exit burr size (thickness and height) and surface roughness during milling of 6601-T6 aluminum alloy. Desirability function, Di(x), is then proposed for multiple response optimization. Optimum setting levels of process parameters are determined for simultaneous minimization of surface roughness and exit burr thickness and height. It was found that the changes in feed per tooth and tool geometry and coating have significant effects on variation of Di(x).Copyright

EXPERIMENTAL INVESTIGATION AND MODELING OF MILLING BURRS

The burr formation is one of the most common and undesirable phenomenon occurring in machining operations which reduces assembly and machined part quality. Therefore, it is desired to eliminate the burrs or reduce the effort required to remove them. This paper presents the results of an experimental study and describe the influence of cutting parameters on slot milling burrs, namely top burrs and exit burrs. Statistical methods are also used to determine the controllability of each burr. A computational model is then proposed to predict the exit up milling side burr thickness based on cutting parameters and material properties such as yield strength and specific cutting force coefficient that are the only unknown variables in the model. The proposed computational model is validated using experimental results obtained during slot milling of 2024-T351 and 6061-T6 aluminium alloys.

Machining Burrs Formation & Deburring of Aluminium Alloys

Although the machinability of most aluminium alloys can be classified as relatively easy when the tool wear and the cutting energy are considered, these materials could however raise some concerns when the chip formation and the burr formation are of concern. Burr formation, a phenomenon similar to chip generation, is a common problem that occurs in several industrial sectors, such as the aerospace and automobile sectors. It has also been among the most troublesome impediments to high productivity and automation, and large‐ ly affects the machined part quality. To ensure competitiveness, precise and burr-free com‐ ponents with tight tolerances and better surface finish are demanded. Intensive research conducted during the last decades has laid out the mechanisms of burr formation and de‐ burring in a very comprehensive fashion, and has introduced integrated strategies for burr prevention and minimization. Despite all the improvements realized, there are still many challenges encountered in understanding, modeling and optimizing the burr formation process and size, through production growth and cycle time reduction. Furthermore, acquir‐ ing a solid knowledge on deburring methods and the links between them and burr size is strongly recommended.

Milling burr size estimation using acoustic emission and cutting forces

Burr formation is one of the main concerns usually faced by machining industries. Its presence leads to additional part edge finishing operations that are costly and time consuming. Burrs must be removed as they are source of dimensional errors, jamming and misalignment during assembly. In many cases burrs may injure workers during handling of machined part. Due to burr effect on machined part quality, manufacturing costs and productivity, more focus has been given to burr measurement/estimation methods. Large number of burr measurement methods has been introduced according to various criteria. The selection of appropriate burr size estimation method depends on number of factors such as desired level of quality and requested measuring accuracy. Traditional burr measurement methods are very time consuming and costly. This article aims to present empirical models using acoustic emission (AE) and cutting forces signals to predict entrance and exit burrs size in slot milling operation. These models can help estimating the burrs size without having to measure them. The machining tests were carried on Al 7075-T6 aluminum alloy using 3 levels of cutting speed, 3 levels of feed rate, 3 levels of cutting tool coating and 2 levels of depth of cut. Mathematical models were developed based on most sensitive AE parameters following statistical analysis, cutting forces and their interaction on predicting the entrance and exit burrs size. The proposed models correlate very well with the measured burrs size data.© 2011 ASME

Burr formation and correlation with cutting force and acoustic emission signals

The principle objective of this work is to present a methodology to evaluate the correlation between burr size attributes (thickness and height) and information computed from acoustic emission and cutting forces signals. In the proposed methodology, cutting force and acoustic emission signals were recorded in each cutting test, and each recorded original acoustic emission signal was segmented into two sections that correspond to steady-state cutting process (cutting signal) and cutting tool exit from the work part (exit signal). The dominant acoustic emission signal parameters including AEmax and AErms were computed from each segmented acoustic emission signal. The maximum values of directional cutting forces (FX, FY and FZ) were also measured in each trial. The experimental verification was conducted on slot milling operation which has relatively more complicated burr formation mechanism than that in many other traditional machining operations. Among slot milling burrs, the top-up milling side burrs and exit burrs along up milling side were largest and thickest burrs which were studied in this work. To evaluate the correlation between signal information and burr size, the computed signal information (5 parameters) and their interaction effects (10 parameters) were used to construct the input parameters of the multiple regression fitted models. Statistical methods were then used to assess the adequacy of individual input parameters and signal information. Using the acoustic emission and cutting force signals information in the input layer of multiple regression models, a high correlation was observed between the predicted and observed values of burr size. It was exhibited that due to complex burr formation mechanism in milling operation and strong interaction effects between cutting process parameters, no systematic relationship can be formulated between the milling burrs.

Experimental investigation on part quality and metallic particle emission when milling 6061-T6 aluminium alloy

The quality of machining operations has a direct relationship with machined part quality and workshop air quality. The main characteristics that describe the machined part quality are burr size and surface finish, while fine particles are also considered as air quality characteristics in machining operations. In the present study, four main surface finish parameters (Ra, Rt, Rz and Rq), burrs size and mass concentration of metallic particles in milling of 6061-T6 aluminium alloy are investigated. The machining factors considered to build the experimental plan are cutting tool coating, insert nose radius, cutting speed and feed per tooth. The statistically significant responses to variation of process parameters and factors governing them are presented.

Burr Size Minimization When Drilling 6061-T6 Aluminum Alloy

The burr formation mechanisms strongly depend on the machining methods as well as cutting conditions. Cutting fluids play significant roles in machining, including reduction of friction and temperature. Using a cutting fluid, however, degrades the quality of the environment and increases machining costs. In the present work, initially the effects of cutting fluid application (dry, mist and flood) and their interaction with cutting parameters on the burr size during drilling of 6061-T6 aluminum alloys were investigated using multi-level full factorial design. Second-order non-linear mathematical models were developed to predict burr height for various lubrication modes. The accuracy of the regression equations formulated to predict burr height when using different lubrication modes has been verified through carrying out random experiments in the range of variation of these variables. A procedure was developed to minimize burr size for drilling holes by presenting the optimal levels of process parameters. Taguchi optimization method based on L9 orthogonal array design of experiment was then used which has shown very accurate process parameters selection that leads to minimum burr height. According to experimental study, it was observed that dry and mist drilling can produce parts with quality comparable with those obtained in wet drilling when using the optimal cutting conditions. In addition, increase in cutting speed and feed rate exhibits a decrease in burr size.© 2012 ASME