The spindle speeds may be calculated for all machining operations once the SFM or MPM is known. In most cases, we are dealing with a cylindrical object such as a milling cutter or a workpiece turning in a lathe so we need to determine the speed at the periphery of this round object. This speed at the periphery (of a point on the circumference, moving past a stationary point) will depend on the rotational speed (RPM) and diameter of the object.

There will be an optimum cutting speed for each material and set of machining conditions, and the spindle speed (RPM) can be calculated from this speed. Factors affecting the calculation of cutting speed are:

Spindle speed becomes important in the operation of routers, spindle moulders or shapers, and drills. Older and smaller routers often rotate at a fixed spindle speed, usually between 20,000 and 25,000 rpm. While these speeds are fine for small router bits, using larger bits, say more than 1-inch (25 mm) or 25 millimeters in diameter, can be dangerous and can lead to chatter. Larger routers now have variable speeds and larger bits require slower speed. Drilling wood generally uses higher spindle speeds than metal, and the speed is not as critical. However, larger diameter drill bits do require slower speeds to avoid burning.

Brown I, Schoop J (2020) The effect of cutting edge geometry, nose radius and feed on surface integrity in finish turning of Ti-6Al4V. CIRP. 87:142–147

a Top view of crater wear and nose profile and b flank wear land and Notch wear of cutting tool based on ISO 3685 (1993)

Tables 5 and 6 displays various tests to select the proper models to fit for surface roughness, and tool life. For all the responses, the quadratic model is appropriate (Prob> F values are less than 0.05 in all the cases).

The spindle speed is the rotational frequency of the spindle of the machine, measured in revolutions per minute (RPM). The preferred speed is determined by working backward from the desired surface speed (sfm or m/min) and incorporating the diameter (of workpiece or cutter).

a Influence of Cutting Speed and Feed on Tool Life. b Influence of Cutting Speed and Depth of Cut on Tool Life. c Influence of Cutting Speed and Nose Radius on Tool Life. a, b, c 3D Surface graph for Tool Life (min)

Turning of AA7075/15 wt% SiC (20-40 μm) composites is very challenging. Selection of proper tool material and geometry is very essential. Tool with high nose radius will provide surface finish and facilitate higher feed rate, but it will reduce the tool life. Hence research is necessary to find out optimum value of nose radius and machining parameters to minimize surface roughness and maximize tool life.

Surface roughness is significantly influence by cutting speed. Surface roughness decreases at high cutting speeds (Fig. 6a). Built up edge (BUE) is formed at low speeds. Chip fracture is also fast at low cutting speed, which results in rough surface. SiC particles do not result in cutting at low speed. SiC particles slides on cutting tool edge and scratch the machined surface. With the increase in speed, the BUE disappears, chip fracture reduces. Hence surface roughness decreases.

e.g. for a cutting speed of 100 ft/min (a plain HSS steel cutter on mild steel) and diameter of 10 inches (the cutter or the work piece)

Myers RH, Montgomery DC (1995) Response surface methodology process and product optimization using design experiments. Wiley, USA

The % increase in surface roughness due to multi response optimization, as compared to \( \mathrm{single}\ \mathrm{objective}\ \mathrm{optimization}=\frac{2.088-2.050}{2.088}\times 100=1.81\% \).

Generally speaking, spindle speeds and feed rates are less critical in woodworking than metalworking. Most woodworking machines including power saws such as circular saws and band saws, jointers, Thickness planers rotate at a fixed RPM. In those machines, cutting speed is regulated through the feed rate. The required feed rate can be extremely variable depending on the power of the motor, the hardness of the wood or other material being machined, and the sharpness of the cutting tool.

Kassim S Al-Rubaie, Yoshimura Humberto N, Biosali de Mello Jose Daniel (1999) Two body abrasive wear of Al-SiC composites.Wear, 233-235:444–4.

SiC particles were uniformly distributed as seen in SEM. Limited particle clustering was observed in composites formed in a semi-solid state. Reinforcing phase resides in the interglobular spaces. No gravity segregation of particles was observed in partially remelted composites even if holding time is more. This also support in homogeneous spreading of SiC particles in AA7075 matrix. No porosity was seen in these structures. Hence, these composites have good mechanical properties. Therefore machining experiments were conducted on these composites.

Figure 9 represent worn cutting tool when turning AA7075/15wt%SiC (20-40 μm). There are uniform abrasion wear tracks, which represent flank wear. Existence of grooves parallel to the cutting direction along tool flank surface shows the dominance of two body abrasion mechanism. This agrees well with the observations of Xiaoping and Seah 2001. Size and number of parallel grooves enhanced with increase in radius of tool nose. When SiC slide it is two body abrasion. When SiC particles roll, wear will mainly depend on plastic distortion of tungsten carbide inserts. Sliding of SiC particle result in microcutting of the AA7075/15wt.%SiC composite. Yan and Wang 1993, was also of similar opinion. This leads to creation of parallel grooves that are seen in SEM. Flank wear is because of abrasive action of the SiC particles. SiC particle of hardness 2700–3500 HV grind the flank face of cutting tools during turning of AA7075/15wt%SiC composites. Weinert 1993, also concluded on same lines.

If variables such as cutter geometry and the rigidity of the machine tool and its tooling setup could be ideally maximized (and reduced to negligible constants), then only a lack of power (that is, kilowatts or horsepower) available to the spindle would prevent the use of the maximum possible speeds and feeds for any given workpiece material and cutter material. Of course, in reality those other variables are dynamic and not negligible, but there is still a correlation between power available and feeds and speeds employed. In practice, lack of rigidity is usually the limiting constraint.

As per literature review, cutting speed, feed, depth of cut and nose radius were taken as process parameters. Responses were surface roughness and tool life. Range of process parameters was finalized based on pilot experiments. These are tabulated in Table 3 (Bhushan 2013).

Green manufacturing desires minimum wastage of materials. It increases productivity, and improve quality of products. Which reduces cost of production. Tool failure is mainly responsible for unpredictable downtime of turning process. Tool failure rises production duration and cost. This problem can be minimized by following a scientific approach (Benardos and Vosniakos 2003). Tool nose radius affect the surface finish. When nose is too sharp the roughness of surface will be high and tool life will reduce. If other factors like material of work, turning speed, and coolant are not taken into consideration, better surface finish will be obtained by tool of large nose radius. This will also allow faster feed rate. According to Suresh 2002 turning tests had shown that large nose radius results in better tool life. This will also permit higher turning speed. A very large nose radius results in chatter. Surface roughness due to preceding revolution while turning, is eliminated in succeeding rotations. Machining of AA7075/15 wt.% SiC composite, to reduce roughness and maximize the tool life is still a challenge. There is urgent need to find the solutions to this challenge. Nose radius is a critical element in determining the value of surface roughness and tool life. Hence further research is necessary.

The ratio of the spindle speed and the feed rate controls how aggressive the cut is, and the nature of the swarf formed.

Depth of cutformula for turning

The phrase speeds and feeds or feeds and speeds refers to two separate parameters in machine tool practice, cutting speed and feed rate. They are often considered as a pair because of their combined effect on the cutting process. Each, however, can also be considered and analyzed in its own right.

SEM micrographs of tungsten carbide inserts before and after turning of AA7075/15 wt.% SiC were taken. Inserts before turning are shown in Fig. 8. Inserts after turning are shown in Fig. 9. Micrographs in Fig. 9 are showing flank wear and crater wear under different machining conditions.

Jurkovic J, Korosec M, Kopac J (2005) New approach in tool wear measuring technique using CCD vision system. Int J Mach Tools Manuf: 45(9):1023–1030

Optimization of process parameters is necessary to achieve better productivity. In this research work, optimization was done to get minimum surface roughness and maximum tool life in turning of AA7075/15 wt.% SiC (20-40 μm) composites using developed mathematical model. Desirability function approach was used.

SEM macrographs of worn out cutting wedges of tungsten carbide tool are shown in Fig. 9. It is seen that cutting tool of nose radius = 1.2 mm at Cutting speed = 90 m/min, Feed = 0.25 mm/rev and DOC =0.6 mm have deeper nose distortion. Removal of insert material is also seen over the cutting edge. This is due to the combined action of cutting force and increase in temperature acting over the cutting edge.

Range of input parameters and values of responses were taken from the experimental results tabulated in Table 4. Optimum solutions are as under;

Considering single objective optimization of cutting parameters the value of surface roughness obtained is 2.088 μm and tool life is 6.72 min.

Experiments were conducted on CNC. AA7075/15 wt.% SiC. 30 mm diameter and 110 mm length rods were utilized for turning. External turning was done by tungsten carbide inserts. No coolant was used during turning. Roughness and tool life were measured. ANOVA was conducted. Significant process parameters were identified and their interaction effects were studied. Experimental results for turning of AA7075/15 wt.% SiC are tabulated in Table 4. These are the average values of three readings. Wear of inserts was measured from SEM microstructure. Tool life was calculated from wear of inserts.

Surface roughness was minimized and tool life was maximized through desirability analysis. Cutting parameters were allowed to vary from lower limit to upper limit. Constraints utilized for optimization of parameters are tabulated in Table 10. Surface roughness is given more importance than tool life, since industrial requirement in turning the AA7075/15 wt.% SiC composite demands more emphasis on the minimum surface roughness than maximum time tool.

Speeds and feeds have been studied scientifically since at least the 1890s. The work is typically done in engineering laboratories, with the funding coming from three basic roots: corporations, governments (including their militaries), and universities. All three types of institution have invested large amounts of money in the cause, often in collaborative partnerships. Examples of such work are highlighted below.

ISO 4287 (1997) Geometrical Product Specifications (GPS)—Surface Texture: Profile Method—Terms, Definitions and Surface Texture Parameters. International Organisation for Standardisation, Geneva

Machinability ratings can be used in conjunction with the Taylor tool life equation, VTn = C in order to determine cutting speeds or tool life. It is known that B1112 has a tool life of 60 minutes at a cutting speed of 100 sfpm. If a material has a machinability rating of 70%, it can be determined, with the above knowns, that in order to maintain the same tool life (60 minutes), the cutting speed must be 70 sfpm (assuming the same tooling is used).

Some materials, such as machinable wax, can be cut at a wide variety of spindle speeds, while others, such as stainless steel require much more careful control as the cutting speed is critical, to avoid overheating both the cutter and workpiece. Stainless steel is one material that hardens very easily under cold working, therefore insufficient feed rate or incorrect spindle speed can lead to less than ideal cutting conditions as the work piece will quickly harden and resist the tool's cutting action. The liberal application of cutting fluid can improve these cutting conditions; however, the correct selection of speeds is the critical factor.

Tool life decrease due to increase of feed and depth of cut (Fig. 7a & b). If the feed is lower, less number of SiC particles will be in contact with the tool, hence tool life will be longer. When depth of cut is more, the tool has a larger length for cutting. Hence tool wear would be more. For this reason lower value of depth of cut, is to be taken for longer tool life.

Zhao T, Zhou JM, Bushlya V, Ståh JE (2017) Effect of cutting edge radius on surface roughness and tool wear in hard turning of AISI 52100 steel. Int J Adv Manuf Technol 91:3611–3618

Choudhury SK, Bartarya G (2003) Role of temperature and surface finish in predicting tool wear using neural network and design of experiments. Int J Mach Tools Manuf 43:747–753

AA7075/15 wt.% SiC composite were selected for machining investigation. Composition of 7075 Al alloy is tabulated in Table 1. Composite AA7075/15 wt.% SiC was made by stir casting process (bhushan and kumar 2011).

Suresh PVS (2002) A genetic algorithmic approach for optimization of surface roughness prediction model. Int J Machine Tools Manufacture 42:675–680

Quigley O, Monaghan J, Reilly PO (1994) Factors affecting the machinability of an Al/SiC metal matrix composite. J MaterProcess Technol 43:21–36

Cutting speed (also called surface speed or simply speed) is the speed difference (relative velocity) between the cutting tool and the surface of the workpiece it is operating on. It is expressed in units of distance across the workpiece surface per unit of time, typically surface feet per minute (sfm) or meters per minute (m/min).[1] Feed rate (also often styled as a solid compound, feedrate, or called simply feed) is the relative velocity at which the cutter is advanced along the workpiece; its vector is perpendicular to the vector of cutting speed. Feed rate units depend on the motion of the tool and workpiece; when the workpiece rotates (e.g., in turning and boring), the units are almost always distance per spindle revolution (inches per revolution [in/rev or ipr] or millimeters per revolution [mm/rev]).[2] When the workpiece does not rotate (e.g., in milling), the units are typically distance per time (inches per minute [in/min or ipm] or millimeters per minute [mm/min]), although distance per revolution or per cutter tooth are also sometimes used.[2]

Ibrahim C, Turker M, Seker U (2004) Evaluation of tool Wear when machining SiC reinforced Al-2014 alloy matrix composites. Mater Design 25:251–255

ISO 3685 specifies a flank wear width of 0.76 mm for rough turning and 0.38 mm for fine turning (ISO 3685 1993). After turning inserts were examined by SEM. Duration of machining as per above specifications was taken as the tool life.

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Most metalworking books have nomograms or tables of spindle speeds and feed rates for different cutters and workpiece materials; similar tables are also likely available from the manufacturer of the cutter used.

Kwon Y, Fischer GW (2003) A novel approach to quantifying tool wear and tool life measurements for optimal tool management. Int J Mach Tools Manuf 43:359–368

Wong YS, Nee AYC, Li XQ, Riesdorf C (1997) Tool condition monitoring using laser scatter pattern. J Mater Process Technol 63:205–210

Figure 8 shows the rake face and flank face of tungsten carbide inserts of nose radius 0.4 mm, 0.8 mm and 1.2 mm before turning. Figure 9 gives the comparison of tungsten carbide inserts (rake face and flank face) after machining of nose radius 0.4 mm and 1.2 mm under same machining conditions i.e. Cutting speed = 90 m/min, Feed = 0.25 mm/rev, DOC =0.6 mm. Flank wear and Crater wear of carbide inserts with nose radius of 1.2 mm are more, as compared to nose radius 0.4 mm.

CNC Turning Machine (Model TC 20) was used for conducting the experiments. Figure 2 shows this machine. Parameters are tabulated in Table 2.

Type of tool wear that affects the nose radius area, also affects the surface roughness of workpiece. Nose wear also takes place in nose area of cutting tool. Therefore nose wear also affect the roughness of the component. But, investigation about the influence of nose wear on the roughness for MMCs is hardly found in literature. Therefore, life of turning tool and roughness of component have been found out to investigate their correlation in turning operation.

Figure 5 shows the microstructure of AA7075/15 wt.% SiC composite. In this structure, SiC particles are uniformly distributed in the AA7075 matrix, without indicating any porosity.

Xiaoping L, Seah WKH (2001) Tool wear acceleration in relation to Workpiece reinforcement percentage in cutting of metal matrix composites. Wear. 247:161–171

Green manufacturing demands least wastage. Minimum chip formation reduces adverse effect on environment. Nose radius has a major role in reducing development of chips. Selection of proper nose radius and machining parameters will reduce amount of chip, therefore protect the environment. In finish turning of Al alloy-SiC, nose radius wear mainly affect the surface feature of the final product. It is owing to the direct contact between the area of tool nose and the SiC particles during turning. This paper is focused on influence of tool nose radius and machining parameters on surface quality of AA7075/15 wt.% SiC (20 - 40 μm) composites and tool life of tungsten carbide inserts while dry turning. Response surface method (RSM) was utilized to find the roughness and tool life under numerous turning situations. Considering the single objective optimization of turning parameters, minimum roughness of 2.088 μm, was achieved at nose radius of 1.2 mm and maximum tool life of 6.72 min, was obtained at nose radius of 0.4 mm. Multi objective optimization by desirability analysis for minimum roughness and the maximum life of tool has shown that suitable value of nose radius is 0.4 mm. Multi objective optimization of both roughness of surface and life of tool results in 1.81% increase in surface roughness and 10.11% decrease in tool life. Abrasion was mainly found to be responsible for wear of tungsten carbide inserts, while turning of AA7075/15 wt.% SiC (20 - 40 μm) composites. Novelty of this research work is that so far no one has investigated impact of nose radius and machining parameters on surface roughness, tool wear and tool life during turning of AA7075/15 wt.% SiC composites. Outcome of this research work will be useful for vehicle, aeroplane, space and ship industry.

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Bhushan, R.K. Impact of nose radius and machining parameters on surface roughness, tool wear and tool life during turning of AA7075/SiC composites for green manufacturing. Mech Adv Mater Mod Process 6, 1 (2020). https://doi.org/10.1186/s40759-020-00045-7

Yan B-H, Wang C-C (1993) Machinability of SiC particle reinforced aluminium alloy composite material. Light Metal 43(4):187–192

Multi objective optimization solutions for the minimum surface roughness and the maximum tool life are given in Table 11. Solution 1 with desirability value of 0.877 is selected. In this, the optimum values of cutting speed, feed, depth of cut and nose radius are 148.05 m/min, 0.16 mm/rev, 0.23 mm and 0.40 mm respectively.

Speed-and-feed selection is analogous to other examples of applied science, such as meteorology or pharmacology, in that the theoretical modeling is necessary and useful but can never fully predict the reality of specific cases because of the massively multivariate environment. Just as weather forecasts or drug dosages can be modeled with fair accuracy, but never with complete certainty, machinists can predict with charts and formulas the approximate speed and feed values that will work best on a particular job, but cannot know the exact optimal values until running the job. In CNC machining, usually the programmer programs speeds and feedrates that are as maximally tuned as calculations and general guidelines can supply. The operator then fine-tunes the values while running the machine, based on sights, sounds, smells, temperatures, tolerance holding, and tool tip lifespan. Under proper management, the revised values are captured for future use, so that when a program is run again later, this work need not be duplicated.

Design of experimentation technique viz. RSM was used for investigating the effect of four process parameters on surface roughness and tool life, while turning of AA7075/15 wt% SiC composite. In RSM relationship between process parameters and responses is achieved with the various desired criteria. Importance of process parameters on the coupled response was also find out (Myers and Montgomery 1995). Thirty numbers of experiments were conducted as per, face centered central composite design (FCCCD) for four variables at three levels. These are depicted in Table 4.

Depth of cutformula

Experimental data (Table 4) was utilized to obtain second order regression coefficient. Insignificant coefficients terms (based on ANOVA) were omitted from the equations.

Hua Y, Liu Z (2018) Effects of cutting parameters and tool nose radius on surface roughness and work hardening during dry turning Inconel 718. Int J Adv Manuf Technol 96:2421–2430

Surface condition of machined component is mainly affected by cutting speed, feed, depth of cut and nose radius for a given machine tool and work piece set-up. SiC particles in the AA7075/15 wt.% SiCp (20-40 μm) composites are also responsible for production of semi-continuous types of chips. It start with initiation of macro- cracks on free surface of the chips. This results in bend formation, which in turn pull out the SiC particles and causes creation of small voids on the machined surface. This is also one of the causes of poor surface finish while turning of Al/SiC−MMC. Sahin and Sur 2004 was also of the same opinion.

a Influence of Cutting Speed and Feed on Roughness. b Influence of Cutting Speed and Depth of Cut on Roughness. c Influence of Cutting Speed and Nose Radius on Roughness. a, b, c 3D Surface graph for Surface Roughness (μm)

Moon HK (1990) Rheological behaviour and microstructure of ceramic particulate – aluminium alloy composites. PhD Thesis. MIT, Cambridge

This formula[14] can be used to figure out the feed rate that the cutter travels into or around the work. This would apply to cutters on a milling machine, drill press and a number of other machine tools. This is not to be used on the lathe for turning operations, as the feed rate on a lathe is given as feed per revolution.

Tool life decreases with increase of nose radius (Fig. 7c). When nose radius is more, part of the tool cutting edge, in contact with the composite will increase. Because of this large number of SiC particles come in contact with tool edge and abrade the tool, which results in reduction of tool life.

Risbood KA, Dixit US, Sahasrabudhe AD (2003) Prediction of surface roughness and dimensional deviation by measuring cutting forces and vibrations in turning process. J Mater Process Technol 132:203–214

Grinding wheels are designed to be run at a maximum safe speed, the spindle speed of the grinding machine may be variable but this should only be changed with due attention to the safe working speed of the wheel. As a wheel wears it will decrease in diameter, and its effective cutting speed will be reduced. Some grinders have the provision to increase the spindle speed, which corrects for this loss of cutting ability; however, increasing the speed beyond the wheels rating will destroy the wheel and create a serious hazard to life and limb.

As with meteorology and pharmacology, however, the interrelationship of theory and practice has been developing over decades as the theory part of the balance becomes more advanced thanks to information technology. For example, an effort called the Machine Tool Genome Project is working toward providing the computer modeling (simulation) needed to predict optimal speed-and-feed combinations for particular setups in any internet-connected shop with less local experimentation and testing.[15] Instead of the only option being the measuring and testing of the behavior of its own equipment, it will benefit from others' experience and simulation; in a sense, rather than 'reinventing a wheel', it will be able to 'make better use of existing wheels already developed by others in remote locations'.

Two experiments (no 1 and 24) were selected out of 30 experiments. Regression equations were validated by comparing 03 experimental data with data obtained by putting the same experimental conditions in the regression equations. Comparison is tabulated in Table 9. There is close correlation between experimental data and data obtained by regression equation. Which validate the developed regression equations. There is 0.8 to 10% variation. This means 90 to 99.2 confidence level. Therefore model is accurate and satisfactory.

Scientific study by Holz and De Leeuw of the Cincinnati Milling Machine Company[17] did for milling cutters what F. W. Taylor had done for single-point cutters.

Feed rate is the velocity at which the cutter is fed, that is, advanced against the workpiece. It is expressed in units of distance per revolution for turning and boring (typically inches per revolution [ipr] or millimeters per revolution). It can be expressed thus for milling also, but it is often expressed in units of distance per time for milling (typically inches per minute [ipm] or millimeters per minute), with considerations of how many teeth (or flutes) the cutter has then determined what that means for each tooth.

Schematically, speed at the workpiece surface can be thought of as the tangential speed at the tool-cutter interface, that is, how fast the material moves past the cutting edge of the tool, although "which surface to focus on" is a topic with several valid answers. In drilling and milling, the outside diameter of the tool is the widely agreed surface. In turning and boring, the surface can be defined on either side of the depth of cut, that is, either the starting surface or the ending surface, with neither definition being "wrong" as long as the people involved understand the difference. An experienced machinist summed this up succinctly as "the diameter I am turning from" versus "the diameter I am turning to."[4] He uses the "from", not the "to", and explains why, while acknowledging that some others do not. The logic of focusing on the largest diameter involved (OD of drill or end mill, starting diameter of turned workpiece) is that this is where the highest tangential speed is, with the most heat generation, which is the main driver of tool wear.[4]

Multi response optimization of surface roughness as well as tool life, will naturally result in some compromise, as both the responses are to be optimized simultaneously. Multi response optimized values of surface roughness and tool life are 2.551 μm and 6.04 min. This results 1.81% increase in surface roughness and 10.11% decrease in tool life. The optimum values of cutting speed, feed, depth of cut and nose radius are 148.05 m/min, 0.16 mm/rev, 0.23 mm and 0.40 mm respectively after multi response optimization.

Crater wear creates a crater on face of the tool. This is due to striking of SiC particles. Notch wear occurs due to reaction between tool faces and coolant (Stephenson and Agapiou 1997). Notch wear growth on the tool face causes damage of the cutting tool. Severe nose wear may result in sudden tool failure (Dimla 2000). Wear in nose area is due to flank wear and notch wear (Dimla 2000; Jurkovic et al. 2005). Figure 1a shows them. Kwon and Fischer 2003, reported that in turning operation, nose wear affects the surface of component.

Abrasion is the main form of tungsten carbide inserts wear for turning of hard SiC particle-reinforced AA7075/15wt%SiC (20-40 μm) composite. Tool life is mainly affected by hardness and weight fraction of SiC particle in the composites. Experiments have confirmed that tool wear increases with increase in hardness and weight fraction of reinforcement particles. When particles are coarser, tool wear further increases. Which reduces the tool life. Our findings are similar to that of Quigley et al. 1994.

Stephenson DA, Agapiou JS (1997) Metal Cutting Theory and Practice. Marcel Dekke, Inc., New York ISBN: 0–8247–9579-2(1997)641–643

A study on the effect of the variation of cutting parameters in the surface integrity in turning of an AISI 304 stainless steel revealed that the feed rate has the greatest impairing effect on the quality of the surface, and that besides the achievement of the desired roughness profile, it is necessary to analyze the effect of speed and feed on the creation of micropits and microdefects on the machined surface.[18] Moreover, they found that the conventional empirical relation that relates feed rate to roughness value does not fit adequately for low cutting speeds.

Flank wear occurs due to abrasion. Flank wear decreases accuracy of machined parts, because it results in damage of the cutting tool (Stephenson and Agapiou 1997). Flank wear land width (VBB) displayed in Fig. 1b, is used to decide tool life.

Depth of cut definitionin lathe machine

Figure 7a shows plot of tool life v/s cutting speed and feed. Tool life decreases with the increase in cutting speed. Increase in feed sharply decreases the tool life.

The main mechanism of tool wear in turning of AA7075/15wt.%SiC composite are two-body and three-body abrasion. The abrasive wear of the tungsten carbide rises when the nose radius increases. This reduces tool life.

Pavel R, Marinescu J, Deis M, Pillar J (2005) Effect of tool wear on surface finish for a case of continuous and interrupted hard turning. J Mater Process Technol 170:341–349

Scanning electron microstructure (SEM) of AA7075 is shown in Fig. 4. Grains are distributed uniformly. Grain distribution is dendritic at few places. Higher stirring speed and shorter period during processing produced smaller grains (Moon 1990).

Figure 10 displays composite desirability of surface roughness and tool life. This value is gained by using Eqs. 1 and 2. Composite desirability value is 0.88 in Fig. 10. Which is suitable to get minimum surface roughness and the maximum tool life. Figure 11 displays the contour graph of surface roughness at maximum desirability value. In this figure predicted value of surface roughness is 2.55 μm, in the range of 2.113 to 4.754 μm after the multi response optimization. Figure 12 displays the contour graph of tool life at maximum desirability value. In this figure predicted value of tool life is 6.04 min, in the range of 0.6 to 6.5 min, after the multi response optimization.

Figure 6b shows the effect of cutting speed and depth of cut on surface roughness. Increase in depth of cut increases the surface roughness in turning of AA7075/15wt.%SiC (20-40 μm). Better surface roughness could be obtained only at lower value of depth of cut. Figure 6c indicate the effect of cutting speed and nose radius on surface roughness. Surface roughness decreases with increase in nose radius. Chip thinning is because of reduction in feed or increase in tool nose radius. This phenomena results in elongation of chip in addition to the thinning effect. Machining with lower chip thickness generally leads to better surfaces.

Chip thickness varies between zero and a maximum value, when tool with large nose radius is used. This try to plough a large portion of the chips rather than shearing it. This ploughing decreases the surface roughness (Fig. 6c). A large nose radius lessens the saw tooth effect of feed marks and appreciably reduces the surface roughness. An excess nose radius is how ever harmful, because it can cause vibration and chatter.

Shah D, Bhavsar S (2020) Effect of tool nose radius and machining parameters on cutting force, cutting temperature and surface roughness – an experimental study of Ti-6Al-4V (ELI). Mater Today: Proc 22:1977–1986

In the 1890s through 1910s, Frederick Winslow Taylor performed turning experiments[16] that became famous (and seminal). He developed Taylor's Equation for Tool Life Expectancy.

Benardos PG, Vosniakos GC (2003) Predicting surface roughness in machining: a reviw. Int J Machine Tools Manuf 43:833–844

Initially literature review upto year 2020 is presented. This is followed by objectives of present research, novelty of the research work and important types of tool wear. Experimental work includes; details about Materials, machines, tools and Designs of Experiments. Finally results are explained and discussed.

Mannan MA, Kassim AA, Jing M (2000) Application of image and sound analysis techniques to monitor the condition of cutting tools. Pattern Recogn Lett 21:969–979

Dimla DE (2000) Sensor signals for tool wear monitoring in metal cutting operations-a review of methods. Int J Mach Tools Manuf 40:1073–1098

One analogy would be a skateboard rider and a bicycle rider travelling side by side along the road. For a given surface speed (the speed of this pair along the road) the rotational speed (RPM) of their wheels (large for the skater and small for the bicycle rider) will be different. This rotational speed (RPM) is what we are calculating, given a fixed surface speed (speed along the road) and known values for their wheel sizes (cutter or workpiece).

Figures 1a-b represent flank, nose, crater and notch wear. So far flank wear and crater wear are investigated as per ISO 3685 standard (ISO 3685 1993).

Figure 6a represents the surface plot of roughness v/s cutting speed and feed. Figure shows that the increase in cutting speed reduces the surface roughness. Increase in feed first decreases then increases the surface roughness.

Depth of cutCalculator

Sahin Y, Sur G (2004) The Effect of A1203, TIN and Ti(C,N) Based CVD coatings on tool wear in machining metal matrix composites. Surf Coat Technol 179:349–355

"Following World War II, many new alloys were developed. New standards were needed to increase [U.S.] American productivity. Metcut Research Associates, with technical support from the Air Force Materials Laboratory and the Army Science and Technology Laboratory, published the first Machining Data Handbook in 1966. The recommended speeds and feeds provided in this book were the result of extensive testing to determine optimum tool life under controlled conditions for every material of the day, operation and hardness."[4]

Gippan SRT − 6210 (Fig. 3) was used for measurement of surface roughness. Cut-off = 0.8 mm, sampling lengths = 4 mm and driving speed of stylus = 0.5 mm/rev was taken. ISO 4287 standard was used (ISO 4287 1997).

ANOVA was done to statistically analyze the results. Pooled version of ANOVA for surface roughness, and tool life are given in Tables 7 and 8. Results show that for surface roughness, cutting speed (A), feed (B), depth of cut (C), nose radius (D), quadratic terms (B2) and interaction term (CD) are significant terms. For tool life cutting speed (A), feed (B), depth of cut (C), nose radius (D), the quadratic terms (C2, D2) and interaction terms (BD, CD) are significant model terms.

Optimum values of cutting speed, feed, depth of cut and nose radius to maximum tool life (6.72 min) are 90.82 m/min, 0.16 mm/rev, 0.31 mm and 0.43 mm respectively.

The cutting speed is given as a set of constants that are available from the material manufacturer or supplier. The most common materials are available in reference books or charts, but will always be subject to adjustment depending on the cutting conditions. The following table gives the cutting speeds for a selection of common materials under one set of conditions. The conditions are a tool life of 1 hour, dry cutting (no coolant), and at medium feeds, so they may appear to be incorrect depending on circumstances. These cutting speeds may change if, for instance, adequate coolant is available or an improved grade of HSS is used (such as one that includes [cobalt]).

Predominant abrasion was found to be responsible for flank wear. Life of inserts during turning of AA7075/15 wt% SiCp (20-40 μm) composites is also affected by many parameters.

When deciding what feed rate to use for a certain cutting operation, the calculation is fairly straightforward for single-point cutting tools, because all of the cutting work is done at one point (done by "one tooth", as it were). With a milling machine or jointer, where multi-tipped/multi-fluted cutting tools are involved, then the desired feed rate becomes dependent on the number of teeth on the cutter, as well as the desired amount of material per tooth to cut (expressed as chip load). The greater the number of cutting edges, the higher the feed rate permissible: for a cutting edge to work efficiently it must remove sufficient material to cut rather than rub; it also must do its fair share of work.

In woodworking, the ideal feed rate is one that is slow enough not to bog down the motor, yet fast enough to avoid burning the material. Certain woods, such as black cherry and maple are more prone to burning than others. The right feed rate is usually obtained by "feel" if the material is hand fed, or by trial and error if a power feeder is used. In thicknessers (planers), the wood is usually fed automatically through rubber or corrugated steel rollers. Some of these machines allow varying the feed rate, usually by changing pulleys. A slower feed rate usually results in a finer surface as more cuts are made for any length of wood.

Cutting speeddefinition

Considering single objective optimization of cutting parameters, the value of surface roughness obtained is 2.050 μm and tool life is 6.52 min. Multi response optimization of both surface roughness and tool life has resulted in some increase in surface roughness and decrease in tool life. This has been calculated as under;

Nose radius and machining parameters play important role for surface roughness of composite and life of tool during turning. Following are the conclusions of this research work.

Investigation of surface characteristics and dimensions of component during machining really needed attention, because surface characteristics and dimensions influence the working of the components (Risbood et al. 2003). Worn cutting tool can be distinguished from an unworn cutting tool by monitoring the profile of workpiece (Mannan et al. 2000). Choudhury and Bartarya 2003 concluded that surface roughness decreased with increase in flank wear. Pavel et al. 2005, found that profile of component is replica of the tool edge profile. As per their observation increase in flank wear land width (VBB) resulted in decrease in roughness. Whereas increase in notch wear increased roughness. They found that notch wear and flank wear affect the surface roughness. However, Wong et al. 1997 observed that flank wear land width and surface roughness are not correlated. Kwon and Fischer 2003 proposed a tool wear index (TWI) to find out the roughness. But in the TWI roughness is a function of time. Roughness increases with period of machining. This differs with the observations of [Choudhury and Bartarya 2003; Pavel et al. 2005; Wong et al. 1997]. Kassim et al. 1999 stated that tool wear, based on the machining condition, affect roughness. Wong et al. 1997 stated that flank wear is not a dependable parameter to forecast roughness. Impact of cutting edge radius on surface roughness and tool wear was examined. CBN, cutting tools with nominal edge radius, 20, 30, and 40 μm, were used. Cutting edge radii were characterized with optical microscope. Variation of edge radius was calculated. Experiments were performed to assess effect of cutting edge radius on surface quality and tool wear under different machining conditions. Three-level and two-factor experiments were planned in test. Variations tend to be smaller with rise of nominal value of edge radius. Moreover, results showed that edge radii have a considerable effect on surface roughness and tool wear. Considering all factors, cutting tool with nominal edge radius of 30 μm shows better machining performance among three groups of cutting tool in hard turning of AISI52100 steel (Zhao et al. 2017). Influence of cutting speed, feed rate, and tool nose radius on machined surface roughness, microhardness, and degree of work hardening of Inconel 718, were examined. Dry turning tests were conducted using three different cutting speeds, three different feed rates, and two cutting tools with different nose radius. Results showed that feed rate and tool nose radius have dominant influence on machined surface roughness. Degree of work hardening was strengthened as cutting speed and feed rate increased. Still, degree of work hardening decreased considerably when larger tool nose radius was used (Hua and Liu 2018). Impact of cutting speed, feed, depth of cut and tool nose radius on cutting temperature, surface roughness and cutting force were examined for turning of Ti-6Al-4 V (ELI). Mathematical models for cutting temperature, surface roughness and cutting force were established from experimental data using RSM. ANOVA test was conducted to assess contribution of parameters. Developed model was interfaced with particle swarm optimization to minimize responses (Shah and Bhavsar 2020). To understand impacts of cutting edge micro-geometries on surface integrity, experimental were conducted for a varied range of cutting tool geometries and feeds. Scanning laser interferometry was used in conjunction with profile-analysis algorithm to analyse, characterize, and verify geometry of complex cutting edge micro-geometries. Near surface nanostructure, and surface roughness of produced surfaces were characterized and correlated to varied tool geometries. Scanning laser interferometry examination of surfaces revealed that large hones provided either an increase or decrease in roughness, depending on expected kinematic roughness (Brown and Schoop 2020). Finish dry hard turning (FDHT) of hardened AISI grade die steel D3 was done by PVD-TiN coated (Al2O3–TiCN) mixed ceramic tool insert. Contribution to modeling and optimization of parameters (cutting force, surface roughness, and tool wear) for machinability evaluation was find out. Turning trials were conducted based on Taguchi\'s L18 orthogonal array design of experiments. Regression model was developed, also adequate model prediction was made by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut (Panda et al. 2020).

The machinability rating of a material attempts to quantify the machinability of various materials. It is expressed as a percentage or a normalized value. The American Iron and Steel Institute (AISI) determined machinability ratings for a wide variety of materials by running turning tests at 180 surface feet per minute (sfpm). It then arbitrarily assigned 160 Brinell B1112 steel a machinability rating of 100%. The machinability rating is determined by measuring the weighed averages of the normal cutting speed, surface finish, and tool life for each material. Note that a material with a machinability rating less than 100% would be more difficult to machine than B1112 and material and a value more than 100% would be easier.

Friction between the tool and component is responsible for tool wear. High turning speed would compel the SiC particles to scrape the tool. Continuous impact will vibrate the tool violently. It will result in breaking of the tool. Therefore tool life will reduce (Fig. 7a). Hence turning is to be done at lower speed. At lower cutting speed, the machining time may be lengthened but tool life is more. But machining efficiency is less and the machined quality is poor.

Cutting speed and feed rate come together with depth of cut to determine the material removal rate, which is the volume of workpiece material (metal, wood, plastic, etc.) that can be removed per time unit.

Above literature review show that research work has been done about impact of nose radius on various grades of steels, while machining. Therefore research gaps are; investigation about the importance of nose radius during turning of AA7075 / SiC composite, investigation about effect of nose radius and machining parameters on surface roughness of AA7075 / SiC, wear and life of carbide tools. The present work is different from other researcher’s work in a way that so far no one has investigated the impact of nose radius and machining parameters on surface roughness and tool life during turning of AA7075 /15 wt.% SiC (particle size 20 to 40 μm). This research work has been taken up with the following objectives.

For a given machining operation, the cutting speed will remain constant for most situations; therefore the spindle speed will also remain constant. However, facing, forming, parting off, and recess operations on a lathe or screw machine involve the machining of a constantly changing diameter. Ideally, this means changing the spindle speed as the cut advances across the face of the workpiece, producing constant surface speed (CSS). Mechanical arrangements to effect CSS have existed for centuries, but they were never applied commonly to machine tool control. In the pre-CNC era, the ideal of CSS was ignored for most work. For unusual work that demanded it, special pains were taken to achieve it. The introduction of CNC-controlled lathes has provided a practical, everyday solution via automated CSS Machining Process Monitoring and Control. By means of the machine's software and variable speed electric motors, the lathe can increase the RPM of the spindle as the cutter gets closer to the center of the part.

Excessive spindle speed will cause premature tool wear, breakages, and can cause tool chatter, all of which can lead to potentially dangerous conditions. Using the correct spindle speed for the material and tools will greatly enhance tool life and the quality of the surface finish.

When calculating for copper alloys, the machine rating is arrived at by assuming the 100 rating of 600 SFM. For example, phosphorus bronze (grades A–D) has a machinability rating of 20. This means that phosphor bronze runs at 20% the speed of 600 SFM or 120 SFM. However, 165 SFM is generally accepted as the basic 100% rating for "grading steels".[12] Formula Cutting Speed (V)= [πDN]/1000 m/min Where D=Diameter of Workpiece in meter or millimeter N=Spindle Speed in rpm

Panda A, Das SR, Dhupal D (2020) Machinability investigation and sustainability assessment in FDHT with coated ceramic tool. Steels Composite Struct 34(5):681–698

Definition of depth of cutin machining

Tool life of tungsten carbide inserts reduced with the increase in cutting speed. Increase in feed sharply reduces the tool life of inserts. This was because at higher feed more number of SiC particles come in contact with insert. The rise in depth of cut first increases then reduces the tool life of tungsten carbide inserts in turning of AA7075/15wt.%SiC. Tool life decreases as nose radius increases. Tool life was the maximum at nose radius of 0.4 mm.

Feed anddepth of cut

The exact RPM is not always needed, a close approximation will work. For instance, a machinist may want to take the value of π {\displaystyle {\pi }} to be 3 if performing calculations by hand.

Bhushan RK, Kumar S (2011) Influence of SiC particles distribution and their weight percentage on 7075 Al alloy. J Mater Eng Perform 20(2):317–323

Figure 7b shows the effect of cutting speed and depth of cut on tool life. Increase in depth of cut first increases then decreases the tool life in machining of AA7075/15wt%SiC. Figure 7c shows the effect of cutting speed and nose radius on tool life. From the figure, it is seen that the tool life reduces at high value of nose radius. Turning is to be carried out at lower value of cutting speed, feed and depth of cut to have the maximum tool life.

Impact of nose radius on progress of tool wear is shown in Fig. 9. Flank wear increases with increase in radius of tool. When large nose radius tool is used for turning, chip thickness varies between zero to maximum. This tends to plough major portion of the chips instead of shearing it. Ploughing leads to high stresses and distortion of the layer being cut. Which subsequently causes rise in temperature. Increased cutting edge and volume of tool edge in contact with the material, results in a higher probability of a greater number of abrasive particles coming into contact with, and abrading the cutting tool material. Which leads to severe wear. This is in line with findings of Ibrahim et al. 2004.

Thirty experiments were designed by using FCCCD. These were conducted on CNC machine. Design Expert 2006 was used for selection of appropriate model and development of response surface models. Regression equations were obtained for surface roughness and tool life. Response were plotted to investigate the effect of input process parameters with their second order interactions on response characteristics.

Multi objective optimization through desirability analysis for the minimum roughness and the maximum tool life to predict suitable value of nose radius.

Depth of cutformula for milling

Outside of the context of machine tooling, "speeds and feeds" can be used colloquially to refer to the technical details of a product or process.[3]

Cutting speed may be defined as the rate at the workpiece surface, irrespective of the machining operation used. A cutting speed for mild steel of 100 ft/min is the same whether it is the speed of the cutter passing over the workpiece, such as in a turning operation, or the speed of the cutter moving past a workpiece, such as in a milling operation. The cutting conditions will affect the value of this surface speed for mild steel.

ISO 3685 (1993) Tool-life testing with single-point turning tools, 2nd edn. International Organisation for Standardisation, Geneva

Cutting feeds and speeds, and the spindle speeds that are derived from them, are the ideal cutting conditions for a tool. If the conditions are less than ideal then adjustments are made to the spindle's speed, this adjustment is usually a reduction in RPM to the closest available speed, or one that is deemed (through knowledge and experience) to be correct.

Depth of cut and tool nose radius were main factors affecting surface roughness. Increase in cutting load to insert edge as the higher depth of cut was used, created more severe plastic deformation resulting in a higher surface roughness. Larger tool nose radius (1.2 mm) created much lower surface roughness in comparison to smaller tool nose radius (0.4 mm). This was ascribed to increase in contact length between the insert and component, which reduced residual height of feed marks.

Hardness of SiC of particle is 2700–3500 HV. Hardness of tungsten carbide inserts is 1500–1800 HV. If only plane tungsten carbide inserts are used, they cannot machine AA7075/ SiC composites. Hardness of titanium nitride is 2400–2800 HV. Hence titanium nitride coated tungsten carbide inserts were used. Inserts CNMG120404, 120,408 and 120,412 grade 6615 were used for turning of AA7075/15 wt% SiC.

Surface roughness increases by increase in feed rate (Fig. 6a). When feed is increased, normal loads on tool also increase. This will produce heat which in turn increases roughness. Increased depth of cut creates high normal pressure and capture on rake face. This promotes formation of BUE. Therefore, surface roughness increases with increase in depth of cut (Fig. 6b).

Bhushan RK (2013) Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites. J Cleaner Production 39:242–254

The optimum values of cutting speed, feed, depth of cut and nose radius to minimize surface roughness (2.08877 μm) are 191.09 m/min, 0.19 mm/rev, 0.23 mm, 1.19 mm respectively.