Top PDF An investigation of surface roughness in micro-end-milling of metals

An investigation of surface roughness in micro-end-milling of metals

An investigation of surface roughness in micro-end-milling of metals

Abstract. This paper presents an experimental study of the effects of cutting parameters of micro-end-milling process on the machined surface roughness, in order to find the optimal operation conditions for improved surface finish. Three types of metals, namely 6160 aluminum alloy, brass, and AISI 1040 steel, are used as work materials. The effect of material property on the surface roughness is investigated. It is found that under the same machining condition, the machined surface quality of aluminum alloy is the worst, while that of brass is the best. A multiple regression model for the surface roughness is developed, which includes the effects of cutting speed, feedrate, and the interaction between them. Results based on analysis of variance (ANOVA) show that the cutting speed is the most significant factor on surface roughness. The residual analysis indicates that the multiple regression model is valid and agrees with the experimental results.
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EFFECT OF CUTTING SPEED AND FEED RATE ON SURFACE ROUGHNESS OF AISI 316L SS USING END-MILLING

EFFECT OF CUTTING SPEED AND FEED RATE ON SURFACE ROUGHNESS OF AISI 316L SS USING END-MILLING

and worst conditions for observations. It shows the surface topography of the machined AISI 316L stainless steel for both test numbers which includes feed marks, chip particles, voids and material flow rough surface and smooth surface. Figure-2a) shows the finished surface in which the feed marks are not noticeable, uninterrupted and smooth at low feed rate (f = 0.12 mm/rev). Secondly there is no such waviness and ridges on the surface. This is because of the less cutting force which produces low plastic deformation and consequently a smooth surface [17, 18]. On the other hand in Figure-2 b) at high feed rate (f = 0.14 mm/rev) interrupted feed marks which were clearly seen on the surface and some crests and troughs which were produced due to high temperature which was produced in the shear zone and high plastic deformation of the surface which led to the formation of rough surface. The formation of the waves on the surface is might be due to the vibrations produced and also due to the tool wear which made the material to move from one surface machined by one flute of the tool and the second flute respectively. Similarly some micro-cracks were observed on the surface. The micro-cracks were due to the incomplete material removal from the surface [18, 19]. CONCLUSIONS
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Experimental Investigation of Surface Roughness in High Speed Milling of OHNS Steel under MQL Technique using RSM Method

Experimental Investigation of Surface Roughness in High Speed Milling of OHNS Steel under MQL Technique using RSM Method

Alper Uysal et al. (2015) In this study the use of nano MoS2 particles reinforced cutting fluid in MQL milling gave the minimum tool wear and surface roughness due to the lubrication effect of nano MoS2 particles [1]. Kedare S. B et al. (2014) In this research work, The cutting performance of MQL machining is better than that of conventional machining with flood cutting fluid supply because MQL provides the benefits mainly by reducing the cutting temperature, which improves cooling effect and results in better surface finish [7]. Y.S.Liao et al. (2007) In this paper, End milling experiments under dry cutting, flood coolant, and MQL conditions were conducted. It is shown that MQL proved beneficial at high speed milling when superior heat resistance coated carbide tool and better cooling ability oil are used. The use of MQL leads to the best performance for all three cutting speeds [17]. M.Rahman et al. (2002) this study, Surface roughness obtained in MQL is comparable to that of flood cooling, while it is better than that of dry cutting [20].
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The effect of cutting parameter on surface roughness during end milling of AISI D2 tool steel

The effect of cutting parameter on surface roughness during end milling of AISI D2 tool steel

The quality of surface machining can be defined as the accuracy of its manufacture with consideration to the dimension stated by the actual size of the part or products. During machining operation there have characteristics information on the machined surface. This characteristics information included of finely spaced micro irregularities left by the cutting tool. Every type of cutting tool leaves in various pattern of machining surface. This arrangement is known as surface irregularities or surface roughness. According to Fallböhmer et al. (2000), Finishing process is a critical part in industry that contribute the highest share of manufacturing lead time for die casting, injection molds, and forging dies. In the certain case of large automotive stamping dies, finish machining has significant part of the total production time (Fallböhmer et al., 1996). Quality surface machining also give the impact on benching time in polishing and grinding is about 15 percent for die casting and injection molds, 20 percent in sheet metal forming dies (Fallböhmer et al., 1996). With the finish the higher of surface quality it will allow a reduction of the benching time. In die and moulds manufactures, the main objective using high speed machining is to minimize a polishing process and decrease the processing lead time time for finishing process. Table 2.1 is showing the averages values of dimensional and form error for dies and mould
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Surface roughness model and parametric optimization in end milling using carbide tools: Response surface methodology and Taguchi approach

Surface roughness model and parametric optimization in end milling using carbide tools: Response surface methodology and Taguchi approach

The experiments were planned using Taguchi’s orthogonal array in the design of experiments (DoE), which helps in reducing the number of experiments. The four process parameters selected in the present investigation were spindle speed, feed rate, and depth of cut and various % wt. of silicon carbide (S). This needs 25 runs and has 24 degrees of freedom (DOFs). In the present experimental study, the material to be machined is LM25 Al alloy reinforced with SiC p particles, at a composition of 5%wt., 10%wt., 15%wt.,

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Modelling and simulation of surface roughness obtain from micro milling by using artificial neural network

Modelling and simulation of surface roughness obtain from micro milling by using artificial neural network

(Theja et al., 2013), reported that the end milling is the widely used operation for metal removal in a variety of manufacturing industries including the automobile and aerospace sector where quality is an important factor in the production of slots, pockets and molds or dies. End mills are used in milling applications such as profile milling, tracer milling, face milling, and plunging. The end mills are used for light operations like cutting slots, machining accurate holes producing narrow flat surfaces and for profile milling operations. End milling is the operation of machining horizontal or vertical surfaces by using an end milling. The operation is usually performed on a vertical milling machine. The principle of end milling shown in Figure 2.4.
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Boric acid role in different Cutting fluids in CNC End Milling by Measuring Surface Roughness

Boric acid role in different Cutting fluids in CNC End Milling by Measuring Surface Roughness

Since the past years various manufacturing operations which includes the machining of metals uses various types of collants and lubricants which are composed of chemicals and other polluants factors. This collants and lubricants which are used, very dangerous and hazardous to the nature and human. This operations includes manufacturing operations like turning, milling, drilling, forming and grinding, forming, sheet métal operations etc. heat generated in the cutting zone results into bad work piece quality and more tool wear. Hence there is need to find and use the alternative coolants and lubricants which will reduce the hazards machining cost and other cost and, factors. In this paper boric acid is mixed with different oils coconut oil, soluble oil and potassium chloride and this mixture is used as cutting fluid and experimentation was done and performance was calculated and results are compared with the conventional and cutting oil without boric acid. Based on the experimental data we can say that boric acid and coconut oil showed that using better performance. New coolants potassium chloride is used in this project that gives more weightage.
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Comparative analysis of aluminium surface roughness in end-milling under dry and minimum quantity lubrication (MQL) conditions

Comparative analysis of aluminium surface roughness in end-milling under dry and minimum quantity lubrication (MQL) conditions

Abstract – In this study an experimental investigation of effects of cutting parameters on surface roughness during end milling of aluminium 6061 under dry condition and minimum quantity lubrication (MQL) condition were carried out. Spindle speed (N), feed rate ( f ), axial depth of cut (a) and radial depth of cut (r) were cutting parameters chosen as input variables in the investigation of the surface roughness quality. The experimental design adopted for this study was the central composite design (CCD) of response surface methodology. Thirty samples were run in a CNC milling machine for each condition and the surface roughness measured using Mitutoyo surface tester. A comparison showing the effects of cutting parameters on the surface roughness for dry and MQL conditions in end-milling of aluminium were evaluated. Surface roughness values for MQL condition were lower with up to 20% reduction when compared to dry conditions. MQL cutting condition was found to be better and more reliable because it is environmentally friendly and gives better surface finish. With the obtained optimum input parameters for surface roughness, production oper- ations will be enhanced.
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A study on surface roughness and burr formation of Al6061 with different spindle speed and federate for small end milling cutter

A study on surface roughness and burr formation of Al6061 with different spindle speed and federate for small end milling cutter

Milling is a well established material removal process for fabricating three dimensional components. With recent advancement in micro and nano devices, mechanical machining can, in principle, be used in the fabrication of micro- scale components. Milling at the micro-scale is able to produce intricate three dimensional features while at the same time satisfy stringent dimensional tolerance and surface finish requirements needed in micro-scale components. However, there are still numerous challenges in micro-cutting to be overcome before it can emerge as a technically sound, economically viable and reliable process to fabricate micro components. In milling, spindle speed, depth of cut, feed rate and cutting speed are the main controlling parameters. There is close relation between the cutting tool workpiece interaction and surface quality [1].
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Application of response surface methodology for prediction and modeling of surface roughness in ball end milling of OFHC copper

Application of response surface methodology for prediction and modeling of surface roughness in ball end milling of OFHC copper

different approaches reviewed were based on machining, experimental design and investigation, and artificial intelligence. Colak et al. (Colak, Kurbanoglu, and Kayacan, 2007) optimized roughness parameters using a generic algorithm for generating end milled surface. A linear equation was proposed for the estimation of the surface roughness that was in terms of parameters such as cutting speed, feed, and depth of cut. Lakshmi et al. (Lakshmi and Subbaiah, 2012) used RSM for modeling and optimization of the end milling process parameters. Average surface roughness for the EN24 grade steel stands for CNC verti- cal machining center. In addition, the second-order model was developed based on the feed, depth of cut, and the speed of cutting. It was shown that the predicted value from the model was in close agreement with the experi- mental values for R a . Jeyakumar et al. (Jeyakumar and
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SURFACE ROUGHNESS INVESTIGATION IN MQCL HARD MILLING OF HARDOX 500 STEEL USING EMULSION-BASED NANOFLUID.

SURFACE ROUGHNESS INVESTIGATION IN MQCL HARD MILLING OF HARDOX 500 STEEL USING EMULSION-BASED NANOFLUID.

[11]. Tran Minh Duc, Tran The Long and Tran Bao Ngoc. Effectiveness of alumina nanofluid on slotting end milling performance of SKD 11 tool steel. Journal of Computational and Applied Research in Mechanical Engineering, Available Online from 19 February 2019, doi:10.22061/JCARME.2019.4041.1484.

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Study of Cutting Forces & Surface Finish in End Milling

Study of Cutting Forces & Surface Finish in End Milling

Surface finish produced on machined surface plays an important role in production. The surface roughness has a vital influence on most important functional properties such as wear resistance, fatigue strength, corrosion resistance and power losses due to friction. Poor surface roughness will lead to the rupture of oil films on the peaks of the micro irregularities which lead to a state approaching dry friction and results in decisive wear of rubbing surface. Therefore finishing processes are employed in machining the surface of many critical components to obtain a very high surface finish.
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Investigation on micro-cutting mechanics with application to micro-milling

Investigation on micro-cutting mechanics with application to micro-milling

Last and the foremost, the underlying cutting mechanics is quite different from what is known in conventional milling. In micro-milling, the cutting edge radius for tungsten carbide tool is normally around several microns. Under this condition, it is comparable in order with the uncut chip thickness and material grain s ize, a variety of issues are arisen including cutting edge radius effect, negative rake angle, minimum chip thickness effect, material microstructure effect and elastic recovery effect, most of which are usually ignored in conventional milling. To thoroughly understand the micro- milling process and give instruction in machining, the fundamental micro-cutting mechanics must be fully investigated and well understood. Moreover, in macro- machining, the product is mostly characterised by dimension, tolerance and surface roughness; while in micro-milling, additional requirements on functional properties (physical, chemical and biological etc.) are attached to the products(Alting et al. 2003). Especially in recent years, structured surfaces with particular designed functions are gaining wide applications (Evans and Bryan 1999, Bruzzone et al. 2008); Structured surfaces may refer to surfaces with a deterministic pattern of usually high aspect ratio geometric features designed to give a specific function (Evans and Bryan 1999; Bruzzone et al. 2008) as shown in Figure 1.3. Functional properties are of the key importance in characterising the product, traditional characterising parameters are not sufficient to define the product any more.
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Investigating the Effect of Machining Parameters on Surface Roughness and MRR of Ti-6Al-4V Titanium Alloy in End Milling

Investigating the Effect of Machining Parameters on Surface Roughness and MRR of Ti-6Al-4V Titanium Alloy in End Milling

In the present work an experimental investigation of machining parameters on Ti -6Al-4V Titanium alloy with carbide coated tool in end milling is carried out and the effect of different cutting parameters like speed, depth of cut , feed rate on the surface roughness and MRR is studied because one can relate quality with surface roughness and productivity with MRR. Application of coolant tends to reduce tool wear and minimize adhesion of the work material on the cutting tool during machining and also improves the surface finish.
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Application of Genetic Algorithm to optimize cutting parameters for minimizing surface roughness in end milling machining process

Application of Genetic Algorithm to optimize cutting parameters for minimizing surface roughness in end milling machining process

Milling is one of the progressive enhancements of miniaturized technologies which has wide range of application in industries and other related areas. Milling like any metal cutting operation is used with an objective of optimizing surface roughness at micro level and economic performance at macro level. In addition to surface finish, modern manufacturers do not want any compromise on the achievement of high quality, dimensional accuracy, high production rate, minimum wear on the cutting tools, cost saving and increase of the performance of the product with minimum environmental hazards. In order to optimize the surface finish, the empirical relationships between input and output variables should be established in order to predict the output. Optimization of these predictive models helps us to select appropriate input variables for achieving the best output performance. In this paper, four input variables are selected and surface roughness is taken as output variable, Genetic algorithm technique is used for finding the optimum set of values of input variables and the results are compared with
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Modelling of the Influence of Tool Runout on Surface Generation in Micro Milling

Modelling of the Influence of Tool Runout on Surface Generation in Micro Milling

radius on the surface roughness in the micro machining, and pointed out that larger cutting edge radius would increase the surface roughness due to the existence of the minimum chip thickness. Oliaei and Karpat [16] inves- tigated the influence of machining parameters on the surface roughness of stainless steel machining. Bissacco et al. [17] studied the size effects on surface generation by ball nose and flat end micro milling of hardened tool steel, and the effects of the increased ratio between cut- ting edge radius and chip thickness have been observed. Sun et  al. [18] studied the relationship among the sur- face roughness, the feed per tooth, as well as the cutter geometry. Li et al. [19] proposed a trajectory-based sur- face roughness model for micro-end-milling and proven capable of capturing the minimum chip thickness, micro tool geometry and process parameters. Based on this model, a surface roughness model with tool wear effect is developed by taking the material removal volume and cutting velocity into account and is experimentally vali- dated. Weule et  al. [20] investigated surface generation in micro-end-milling of steel and concluded that the sur- face roughness had the increasing trend when the feed rate was smaller than the cutting edge radius. Previous research studied the influence of geometry of the cutter, machining parameters, tool wear and minimum cutting chip thickness on the surface generation in micro milling. While the runout of the tool is ignored, which plays an important role in the surface generation in micro mill- ing due to the fact that in micro milling the magnitude of tool runout is comparable with the feed per tooth. In this paper, a surface generation model is proposed consider- ing the tool runout both in axial and radial directions, after that the influence of the runout on the surface gen- eration is studied quantitatively.
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Experimental Study on Machinability of Ti-6Al-4V in Micro End-Milling

Experimental Study on Machinability of Ti-6Al-4V in Micro End-Milling

The above-mentioned problems can be more significant in micro-scale machining of difficult-to-machine materials. However, a limited number of researches on micro-scale machining of difficult-to-machine materials have been studied. Aramcharoen and Mativenga conducted the micro-milling of hardened tool steel in order to investigate the size effect [8]. The results showed that the specific cutting force, surface finish, and burr formation were changed depending on the ratio of undeformed chip thickness to the cutting edge radius. In the case of titanium alloy, Schueler et al. studied the burr formation and surface generation characteristics in the micro end-milling of Ti-6Al-4V and Ti-6Al-7Nb with the micro end-mills having the diameter of 48 um [9]. The massive wavy-type burrs were formed at the low depth of cut, but the surface roughness did not differ according to feed rates solely. Ramesh et al. also investigated the burr formation and surface quality in the micro milling of Ti-6Al-4V [10]. Several types of burr were observed at different locations of the machined groove and the effect of machining parameters on burr size were analyzed. In addition, they reported that surface roughness increased with the increase in spindle speed, feed rate, and depth of cut. Thepsonthi and Özel conducted the multi-objective process optimization in order to obtain optimal process parameters in the micro end-milling of Ti-6Al-4V in terms of the burr formation and surface roughness [11]. They concluded that axial depth of cut is a major process parameter causing top burr formation and feed rate is a major process parameter affecting surface roughness.
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Study on tool wear and surface roughness in end milling of particulate aluminum metal matrix composite: Application of response surface methodology

Study on tool wear and surface roughness in end milling of particulate aluminum metal matrix composite: Application of response surface methodology

Ibrahim Ciftci et al. [9] studied the influence of different particle size of SiC and cutting speed on tool wear and surface roughness during machining of Al/SiC MMC using cubic boron nitride (CBN) cutting tool. The results showed that tool wear was mainly observed on flank side with a strong influence by abrasive reinforcement. Palanikumar [10] developed a model for surface roughness through response surface method (RSM) while machining GFRP (Glass Fibre Reinforced Plastics) composites. Four factors five level central composite rotatable design matrix was employed to carry out the experimental investigation. Analysis of variance (ANOVA) was used to check the validity of the model.
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Effect of Machining Parameters on Surface Roughness of End Milling

Effect of Machining Parameters on Surface Roughness of End Milling

Abstract: This research work deals with the investigation on the effect of process parameters on surface roughness in end milling process. Surface roughness plays an important role in deciding the quality of machining. Mathematical model has been developed to predict the surface roughness in terms of machining parameters such as helix angle of cutting tool, spindle speed, feed rate, and depth of cut. Central composite rotatable second order response surface methodology was employed to create a mathematical model and the adequacy of the model was verified using analysis of variance. The experiments were conducted on stainless steel SS 202 by carbide end mill cutter and the surface roughness was measured using Mituotyo surface test SJ201. The direct and interaction effect of the machining parameter with surface roughness were analyzed, which helped to select the level process parameter in order to ensure quality of end milling.
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Precession of Surface Roughness by CNC End Milling

Precession of Surface Roughness by CNC End Milling

surface plays an important role in production. The surface roughness has a vital influence on most important functional properties like wear resistance, fatigue strength, corrosion resistance and power losses due to friction. Poor surface roughness will lead to the rupture of oil films on the packs of micro irregularities which lead to a state approaching dry friction and results in decisive wear of rubbing surfaces therefore finishing process are employed in machining the surface of many critical components to obtain a very high surface finish. Process variables surface roughness in milling depends on spindle speed, feed, number of flutes, and depth of cut and plan approach angle. Mainly surface finish depends on spindle rpm, feed rate and depth of cut).
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