The aluminium alloys are widely employed in the aeronautical, aerospace and automotive industries due to the fact they provide good heat conductivity, corrosion resistance, high strength to weight ratio even at high temperatures. Cutting fluids are still widely used due to the fact that these materials can commonly show problems associated with the heat generation. However, the growing social preoccupation towards environmental conservation has made it necessary to develop cleaner production technologies as dry machining, in which no cutting fluids are employed. Solid lubricant assisted machining is a novel concept to control the machining zone temperature without polluting the environment. The surface quality of the machined parts is one of the most important product quality characteristics and one of the most frequent customer requirements. The present study focuses on investigating the effect of boric acid powder as solid lubricant on surface quality as well as cutting forces. Experiments have been conducted utilizing Taguchi’s L9 orthogonal array. The influence of machining parameters viz. cutting speed, feed, rake angle and tool nose radius has been investigated. The objective of this research is to find the optimum cutting parameters based on surface roughness, cutting temperature and tool wear.
CONTENTS
ABSTRACT
CONTENTS
LIST OF FIGURES
LIST OF TABLES
CHAPTER-1
INTRODUCTION
1.1 PROJECT BACKGROUND
1.2 PRINCIPLE OF TURNING
1.3 COMPARISION BETWEEN WET AND DRY TURNING
1.4 ALUMENIUM 6061 ALLOY
1.4.1 Application
1.4.2 Composition of Aluminum 6061
1.5 SOLID LUBRICANT
1.6 OBJECTIVE
CHAPTER-2
LITERATURE REVIEW
2.1 Literature review
CHAPTER-3
EXPERIMENTATION
3.1 WORKPIECE DESCRIPTION
3.1.1 Material
3.1.2 Properties
3.2 TOOL DESCRIPTION
3.2.1 Tool Material and Dimensions
3.2.2 Properties of Tool Materials
3.3 MACHINE TOOL SELECTION
3.4 SELECTION OF ENVIRONMENT
3.4.1 Wet Machining
3.4.2 Solid Lubricant Assisted Machining
3.5 MACHINING PARAMETERS
3.5.1 Feed
3.5.2 Cutting Speed
3.5.3 Rake Angle
3.5.4 Nose Radius
3.6 RESPONSE PARAMETERS
3.6.1 Mean Arithmetic Roughness
3.6.2 Tool Temperature
3.6.3 Tool Wear
3.7 TOOL PREPARATION
3.8 DESIGN OF EXPERIMENTS
3.9 CONDUCTION OF EXPERIMENT
3.10 ARRANGMENT FOR TEMPERATURE MEASUREMENT
3.11 ARRANGEMENT FOR SOLID LUBRICANT FEEDING
3.11.1 Experimental Setup For Solid Lubricant Feeding
3.12 MEASUREMENT OF RESPONSE PARAMETERS
3.12.1 Temperature
3.12.2 Roughness
3.12.3 Tool Wear
3.13 CHIP MORPHOLOGY
3.13.1 Chip Morphology Definition and Types
3.13.2 Chips Obtained In Solid Lubricant and Wet Turning
CHAPTER 4
OBSERVATION, ANALYSIS, AND DISCUSSION
4.1 DESCRIPTION OF SOFTWARE TOOLS
4.2 OBSERVATION TABLE
4.3 GENERAL LINEAR REGRESSION MODEL
4.3.1 Regression equation for Mean Arithmetic Roughness
4.3.2 Regression equation for Temperature
4.3.3 Regression equation for Tool Wear
4.4 STATISTICAL ANALYSIS BY ANOVA (ANALYSIS OF VARIANCE)
4.4.1 ANOVA Result for Roughness
4.4.1.1 With Solid Lubricant
4.4.1.2 With Liquid Lubricant
4.4.1.3 Comparison of percentage contribution of input parameters on
4.4.1.4 ss using different lubricant
4.4.2 ANOVA Result for Temperature
4.4.2.1 With Solid Lubricant
4.4.2.2 With Liquid Lubricant
4.5 COMPARISION OF LUBRICANT PERFORMANCE ON THE RESPONSE PARAMETERS
4.5.1 Effect on Surface Roughness
4.5.2 Effect on Tool Temperature
4.6 MAIN EFFECT PLOTS FOR MEAN
4.6.1 Main Effect plot for Roughness
4.6.2 Main Effect plot for Tool Temperature
4.7 OPTIMIZATION OF PARAMETERS USING S/N RATIO
4.7.1 S/N Ratio Plots for Roughness
4.7.1.1 Plot for Solid Lubricant
4.7.1.2 Plot for Liquid Lubricant
4.7.2 S/N Ratio Plots for Temperature
4.7.2.1 Plot for Solid Lubricant
4.7.2.2 Plot for Liquid Lubricant
4.8 ANALYSIS OF TOOL WEAR
4.8.1 Statistical Analysis by ANOVA
4.8.2 Percentage contribution of various parameters in Tool Wear
4.8.3 Main Effect Plot for Tool Wear
4.8.4 Optimization Using S/N Ratio
4.9 . ANALYSIS OF CHIP MORPHOLOGY
CHAPTER 5
CONCLUSION
REFERENCES
LIST OF FIGURES
Figure 1.1 a) A tube
Figure 1.2 b) A cylindrical bar
Figure 1.3 Schematic Diagram of Turning Operation
Figure 3.1 Al-6061 Workpiece
Figure 3.2 Tool Showing Rake Angle and Precision Hole of 01 mm
Figure 3.3 Picture showing specifications of all nine tool set wise
Figure 3.4 Picture showing Conventional Lathe Machine
Figure 3.5 Picture showing Scheme of Experiment and Analysis
Figure 3.6 Arrangement for temperature measurement
Figure 3.7 The photograph of the setup for the solid lubricant feeding and its Schematic diagram
Figure 3.8 Picture showing roughness values for dry and wet turning measured by Taylor Hobson Precision Surface Roughness Testing Machine
Figure 3.9 Picture showing measurement of Flank Wear in Tool
Figure 3.10 Picture showing chip morphology for different experiment sets under dry and wet environment
Figure 4.1 Contribution of Input Parameters on Surface Roughness
Figure 4.2 Comparison of Surface Roughness
Figure 4.3 Comparison of Tool Temperature
Figure 4.4 Main Effect Plot for Roughness with Solid Lubricant
Figure 4.5 Main Effect Plot for Roughness with liquid lubricant
Figure 4.6 Main Effect Plot for Temperature with Solid Lubricant
Figure 4.7 Main Effect Plot for Temperature with liquid lubricant
Figure 4.8 S/N ratio for Roughness in Solid Lubricant assisted turning
Figure 4.9 S/N ratio for Roughness in Liquid Lubricant assisted turning
Figure 4.10 S/N ratio for Temperature in Solid Lubricant assisted turning
Figure 4.11 S/N ratio for Temperature in Liquid Lubricant assisted turning
Figure 4.12 Percentage contribution of various parameters in tool wear
Figure 4.13 Main effect plot for Tool Wear
Figure 4.14 S/N ratio plot for tool wear
Figure 4.15 Sample chips obtained (a) With Liquid Lubricant (b) With Solid Lubricant
LIST OF TABLES
Table 1.1 Details of A16061 Alloy
Table 3.1 Composition of Al6061
Table 3.2 Properties of Al 6061
Table 3.3 Mechanical properties of M-42 HSS Tool Bit
Table 3.4 Experiment design by Taguchi L9 orthogonal array
Table 3.5 Specification of Taylor Hobson Precision Surface Roughness Testing Machine..
Table 3.6 Size and Shape of chips obtained in experiments
Table 4.1 Output Record in presence of liquid lubricant
Table 4.2 Output Record in presence of Boric Acid
Table 4.3 Flank Wear width of various tools
Table 4.4 ANOVA Result for Roughness with Solid Lubricant at a=0.05
Table 4.5 ANOVA Result for Roughness with liquid lubricant at a=0.05
Table 4.6 ANOVA Result for Temperature with solid lubricant at a=0.05
Table 4.7 ANOVA Result for Temperature with liquid lubricant at a=0.05
Table 4.8 Formulae of S/N ratios for different strategies
Table 4.9 ANOVA Result for Tool Wear at a=0.05
Table 4.10 Optimum parameters for the responses
Abstract
The aluminium alloys are widely employed in the aeronautical, aerospace and automotive industries due to the fact they provide good heat conductivity, corrosion resistance, high strength to weight ratio even at high temperatures. Cutting fluids are still widely used due to the fact that these materials can commonly show problems associated with the heat generation. However, the growing social preoccupation towards environmental conservation has made it necessary to develop cleaner production technologies as dry machining, in which no cutting fluids are employed. Solid lubricant assisted machining is a novel concept to control the machining zone temperature without polluting the environment. The surface quality of the machined parts is one of the most important product quality characteristics and one of the most frequent customer requirements. The present study focuses on investigating the effect of boric acid powder as solid lubricant on surface quality as well as cutting forces. Experiments have been conducted utilizing Taguchi’s L9 orthogonal array. The influence of machining parameters viz. cutting speed, feed, rake angle and tool nose radius has been investigated. The objective of this research is to find the optimum cutting parameters based on surface roughness, cutting temperature and tool wear.
CHAPTER 1
INTRODUCTION
• PROJECT BACKGROUND
• OBJECTIVES
1.1 PROJECT BACKGROUND:
Recent developments in different methods of machining have significantly increased the potential for widespread industrial applications of turning. Although a high surface quality has been achieved in earlier investigations widespread industrial application of turning technology necessitated a better understanding of the effects of process parameters on surface quality. A cylindrical bar or a tube can be used as the workpiece for the turning operation.
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Figure 1.1(a) a tube
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Figure 1.1(b) a cylindrical bar
Turning is a very basic operation and produces a cylindrical surface. The tool used for this type of an operation is known as a lathe. The major types of turning operations are:
• Turning of cylindrical and stepped cylindrical surfaces
• Turning of tapered and curved surfaces of revolution
• Turning of screw threads
• Face turning and parting
Materials that can be machined by using turning include Al & its alloys, Mg, Cu, Steel etc.
Significant advances have been seen in cutting tools & machine tools in recent years. Cutting parameters may be specified according to hardness of material and roughness of the surface of a workpiece usually these are cutting speed, rake angle, depth of cut etc. The optimization the experimental studies is done by using the Taguchi method. Then the results of performance will be analyzed by using Variance analysis (ANOVA).
1.2 PRINCIPLE OF TURNING
In a typical turning operation where a workpiece in the form of a cylindrical bar is rotated about the axis of symmetry. The tool is provided with a feed motion parallel to the work axis.
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Figure 1.2 Schematic Turning Operation
Thus, it is easy to see that with respect to the work the tool has a helical motion and analysis encounters an uncut layer of the workpiece. Here, the machining operation is continuous. This operation results in reduced diameter and a new cylindrical surface.
1.3 COMPARISON BETWEEN WET TURNING AND DRY
TURNING
The heat produced during the turning process is critical in terms of work piece quality. Relatively high friction affects in turning cause heat generation that can lead to poor surface quality of machine component. Surface quality of machined parts is affected by many factors such as tool geometry and cutting conditions. The application of conventional cutting fluids create some environment problem such as environment pollution, biological problems to operators, water pollution etc. Further the cutting fluids also incur a major portion of the total manufacturing cost. All these factors prompt investigations on the use of biodegradable cutting fluids or the elimination of cutting fluid.
Machining with solid lubricants and cryogenic coolants are some of the alternative approaches in this direction. Application of solid lubricant in machining has proved to be a feasible alternative to fluid coolants if it can be applied properly. Advancement in modern tribology has identified many solid lubricants (Graphite, Boric Acid Powder, MoS2 etc.) which can sustain and provide lubricity over a wide range of temperatures. If suitable solid lubricant is applied properly, then improved process results may be expected. Therefore, the aim of present investigation is to investigate the effect of solid lubricant, such as boric acid powder, on the surface quality of the machined component.
1.4 ALUMINIUM 6061 ALLOY
1.4.1 APPLICATION
1. Al-6061 is widely used for construction of aircraft structures such as wings and fuselage.
2. Used for yacht construction.
3. Used in automotive parts such as wheel spacers.
4. Used in the manufacture of aluminium cans for the packaging of foodstuffs and beverages.
5. Used in the construction of bicycle frames and components
6. Used in the production of extrusions—long constant-cross-section structural shapes produced by pushing metal through a shaped die.
7. Automotive parts, ATV parts, and industrial parts are just some of the uses as a forging.
Table 1.1 DETAIALS OF Al6061 ALLOY:
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1.5 SOLID LUBRICANT
Dry machining can eliminate cutting fluids with the advancement of the cutting tool materials. Dry machining requires less power and produces a smoother surface than wet turning at specified cutting condition. The most common lubricating solids are Graphite, Molybdenum disulphide and boric acid. MoS2 oxidizes at approximately 750o to MoO3, which acts as an abrasive, greatly reducing in performance. For graphite, the limitation is the loss of the absorbed layer of water with increasing temperature
Boric acid powder has been used as the solid lubricant.
PROPERTIES OF BORIC ACID POWDER:
• Boric Acid H3BO3 % > 99.9
IMPURITIES:
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1.6 OBJECTIVE:
The objectives of the project are:
1. To investigate effect of cutting parameters on surface quality and their comparison in solid & liquid lubricant assisted turning.
2. To investigate effect of cutting parameters on tool temperature and their comparison in solid & liquid lubricant assisted turning.
3. To determine the tool wear (flank wear) and optimization of parameters for tool life.
4. To develop a linear regression model to determine the relationship between response and input parameters.
5. Statistical analysis by ANOVA to determine most significant parameter for various response.
6. Comparison of lubricant performance on the response parameters.
7. To draw the main effect plots for mean response parameters.
8. To analyze the chip morphology by visual inspection.
CHAPTER 2
LITERATURE REVIEW
2.1 LITERATURE REVIEW
Recent developments in machining have significantly increased its potential for widespread industrial applications. However, machining experiences high temperatures due to the friction that exists between the tool and workpiece, and thus influencing the workpiece dimensions and its surface quality. Machining temperatures can be controlled by reducing the friction between tool— workpiece and tool-chip interface with the help of effective lubrication. Cutting fluids are the conventional choice to act as both lubricants and coolants.
Hence, the application of conventional cutting fluids causes several adverse effects, such as environmental pollution, dermatitis to operators, water pollution, and soil contamination during disposal [1, 2, 3]. Further, the cutting fluids also incur a major portion of the total manufacturing cost. All these factors prompt investigations into the use of biodegradable coolants and coolant-free machining. Hence, as an alternative to cutting fluids, researchers experimented with dry machining, coated tools, cryogenic cooling, minimum quantity lubrication (MQL), and solid lubricants.
Dry machining, as the machining of the future, has been reported that it can eliminate cutting fluids with the advancement of cutting tool materials [4]. Dry machining requires less power and produces a smoother surface than wet machining at specified cutting conditions [ 5 ]. In tribological applications of hard protective coatings, the toughness is as important as their hardness; both properties have a great influence on the wear resistance of coated tools [6]. Itakura et al. [ 7 ] conducted dry turning experiments to identify the tool wear mechanisms with a coated cemented carbide tool while machining Inconel 718. During continuous cutting, almost no rake wear but only flank wear appeared. During interrupted cutting, material adhered to the rake face (built-up-edge) is removed, causing the coating film to deteriorate. Jindal et al. [8] studied the relative merits of powder vapour deposition (PVD) TiN, TiCN, and TiAlN coatings on cemented carbide substrate (WC - 6 wt% Co alloy) while turning of Inconel 718. TiAlN and TiCN- coated tools performed significantly better than tools with TiN coatings. However, the choice of the coating, associated coating materials, coating procedure, and the choice of cutting conditions are the main problems with coated tools. Kustas et al. [ 9 ] stud- ied the application of nano-coatings on cutting tools. Multi-layer hard coatings consist very thin layers and exhibits good properties like multi-functional character, moderate residual stress, good adherence, proper hardness-to-toughness ratio, low coefficient of friction, good oxidation resistance, and high thermal and mechanical stability compared to mono-layer coatings. Cryogenic cooling by liquid nitrogen jet provided reduction in average chip—tool interface temperature, high reduction in flank wear, better surface finish, and dimensional accuracy as compared to dry machining of AISI 1060, AISI 1040, E4340C, AISI 4140, and AISI 4037 steels [10- 13 ]. Cryogenic machining by liquid nitrogen with the help of modified tool holder provided longer tool life and more wear resistance compared to dry machining [ 14 ]. With tighter industrial regulations and environmental aspects across the globe, researchers have been working to achieve eco- friendly, sustainable manufacturing. MQL is another promising technique adopted by the researchers. The encouraging results include significant reduction in tool wear, dimensional inaccuracy, and surface rough- ness by MQL mainly through a reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interactions [ 15 ]. In another study, good results are reported in terms of tool wear reduction, surface finish, and dimensional accuracy using clean machining processes with minimum quantity of lubricant, such as MoS2 powder, grease-based graphite mixed with water, and SAE-20 oil in various proportions instead of flooding coolant [ 16, 17 ]. MQL is shown to result in overall superior performance compared to dry and wet turning on the basis of cutting forces, tool life, cutting temperature, and surface finish [ 15, 18 ].
Shaji and Radhakrishnan [ 19 ] investigated the effect of graphite in surface grinding. Improvement in sur- face finish is reported with the application of a solid lubricant. In another study [20], they reported improvement in process results using graphite, calcium fluoride, barium fluoride, and molybdenum trioxide in grinding. Venugopal and Rao [ 21 ], who outlined the surface finish improvement, focused on the application of graphite in grinding SiC. Jianhua et al. [ 22 ] studied the friction coefficient at the tool-chip interface in dry cutting of hardened steel and in cast iron with an Al2O3/TiC/CaF2 ceramic tool and reported a reduction in friction coefficient with the addition of CaF2 solid lubricant. Reddy and Rao [ 23 ] reported that graphite and molybdenum disulfide-assisted end milling process showed considerable improvement compared to machining with a cutting fluid in terms of cutting forces, surface quality, and specific energy. Dilbarg and Rao [ 24 ] studied the use of solid lubricants during hard turning while machining bearing steel with mixed ceramic inserts at different cutting conditions and tool geometry. Results showed 8 per cent to 15 per cent improvement in the surface finish with the use of solid lubricants compared to dry hard turning. Damera and Pasam [25] investigated that Boric Acid improves surface performance by reducing cutting forces and tool wear. Ramana, Ramji, Satyanarayan et al [26] investigated that with decrease in particle size of solid lubricant Boric Acid, surface finish deteriorates with 23.45%, forces increased and the temperature of tool increased. Mishra and Agarwal [27] investigated the effect of graphite as solid lubricant in the zone of machining. Experiments were carried out to investigate the role of solid lubricant such as graphite on the surface finish of the product in machining a AISI 4340 steel by uncoated cemented carbide inserts of different tool geometry under different cutting conditions. Results indicate that the effectiveness of used graphite as a solid lubricant is to an increase of 5% to 25% in the surface quality.
Even though, the application of solid lubricants in machining is reported by several researchers, the usage of boric acid is seldom found in machining. Boric acid’s unique lattice-layered structure makes it a very promising solid lubricant material besides its relatively high load-carrying capacity and low steady-state friction coefficient (0.02). It reduces the shear strength of material at the machining zone.
Under atmospheric pressure, boric acid dehydrates above 170 ◦C and soften at around 400 ◦C, forming a film over the surface on which it is applied. Rao and Krishna [28] studied the influence of solid lubricant particle size on machining performance. Machining performance in terms of cutting forces, cutting temperatures, tool flank wear, and surface roughness was reported at constant cutting conditions while suing graphite and boric acid in dry powder form. These solid lubricants performed well with reduced particle size. Boric acid performance is better to graphite in selected machining conditions.
CHAPTER 3
EXPERIMENTATION
3.1. WORKPIECE DESCRIPTION
3.1.1 MATERIAL
The workpiece material used in our project is Al6061 rod of diameter 22mm. This material was manufactured from Jindal Aluminium Ltd located in Bangalore city. The major elements of workpiece include Aluminium and Silicon copper and Iron are also present in traces.
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Figure 3.1 Al-6061 Workpiece
TABLE 3.1 Composition of Al6061.
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The selection of Al6061 as project material was made on the basis of its wide range of applications in construction of aircraft structures, yacht, automotive parts, bicycle frames and components and in the manufacture of aluminium cans for the packaging of food stuffs and beverages, etc. Its excellent joining characteristics, good acceptance of applied coatings, high strength, good workability and high resistance made us to select aluminium 6061 as the workpiece material. A limited research has been done on Al6061 and solid lubricants and there is a wide scope of work in this area.
3.1.2 PROPERTIES of Al 6061
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3.2 TOOL DESCRIPTION
3.2.1 TOOL MATERIAL AND DIMENSIONS
In Our Experiment Work, M-42 HSS Bit tool (Figure 3.2) was used. The tools were prepared in IGTR (Indo German Tool Room) for precision requirements. The number of tools was 9 and dimensions were 3/8"x3/8"x1.5" (Inches). A 01 mm precision hole upto a distance of 2 mm from tool tip was also made. In principle, the rake angle should be less for efficient cutting and less tool wear.
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Figure 3.2 Tool Showing Rake Angle and Precision Hole of Ø1 mm
The prime requirements of a tool material are that it must maintain a good tool to workpiece wear ratio (relative wear ratio). The selection of the tool material depends primarily upon the specific cutting application and upon the material being machined. HSS tools have good machinability on Al-6061. According to Loladge’s criteria, the tool material must be atleast 1.35-1.5 times harder than the workpiece material and M-42 HSS tools are harder than Al 6061 workpiece material. Hence, they are easy to fabricate in various shapes and dimensions. So, all our design criteria are fulfilled by HSS tool, hence it was selected as tool material.
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Figure 3.3 Picture showing specifications of all 9 tool set wise
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3.2.2 Mechanical Properties of Tool Materials
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3.3 MACHINE TOOL SELECTION
The machine tool we selected for our experiment is Conventional Lathe for turning purpose. It was selected due to its easy availability and operations.
SPECIFICATIONS
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Figure 3.4 Picture showing Conventional Lathe Machine
3.4 SELECTION OF ENVIRONMENT
In the present work two environment were chosen for the purpose of comparison of response parameters viz. wet machining and solid lubricant assisted machining.
3.4.1 WET MACHINING- CUTTING FLUID ASSISTED MACHINING
The Cutting Fluid used in the experiment was Petroleum Based Cutting Fluid and its properties are given below. The introduction of cutting fluid applicability into the experiment was in order to improvise the surface quality of turned workpiece and also to compare the surface quality of workpiece with respect to solid lubricant under same environment and tools. Besides Surface Quality indifference, an appreciable difference in surface temperature of workpiece was also obtained under the two environments.
PROPERTIES
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The Cutting Fluid used in Turning Process serves multiple functions:
1. It acts as a coolant for both the tool and the workpiece.
2. It helps to improve the surface quality of turned Al6061 workpiece.
3.4.2 SOLID LUBRICANT ASSISTED MACHINING
The solid lubricant we used in our experiment was Boric Acid. the properties of Boric acid used are given below. It was used in order to provide a dry environment for conducting experiments. The selection of Boric Acid was due to its functioning over Al6061 workpiece and also less wear of tools.
SPECIFICATION
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IMPURITIES
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3.5 MACHINING PARAMETERS
The Feed, Spindle Speed, Rake Angle and Tool Radius are key process variables that affect the turning of Al6061 workpiece. The parameters have been selected due to significant effect on Aluminium and according to literature review there is a vast scope of research with respect to these input parameters.
3.5.1 FEED
The relatively small movement per cycle of the cutting tool, relative to the work piece in a direction which is usually perpendicular to the cutting speed direction. It is expressed in millimetres per revolution (mm/rev) or millimetres per stroke (mm/stroke). It is more complex element as compared to cutting speed, since it is expressed differently for various operations. For example, in turning and drilling, the feed is the axial advance of the tool along or through the job during each revolution of the tool or job.
3.5.2 CUTTING SPEED
The speed can be defined as the relative surface speed between the tool and the job. It is expressed in metres per minute (mpm). it is thus the amount of length that will pass the cutting edge of the tool per unit of time.
3.5.3 RAKE ANGLE
It is the angle between the face of the tool and a line parallel of the tool and measured in a plane (perpendicular) through the side cutting edge. This angle is positive, if the side cutting edge slopes downwards from the point towards the shank and is negative if the slope of the side cutting edge is reverses. So this angle gives slope of the face of the tool from the nose towards the shank. A positive rake angle is recommended when machining low strength material shafts of small diameters and cutting at low speeds.
3.5.4 NOSE RADIUS
Nose radius is favourable to long tool life and good surface finish. A sharp point on the end of a tool is highly stressed, short lived. There is an improvement in surface finish and permissible cutting speed as nose radius is increased from zero value. Too large nose radius will induce chatter.
3.6 RESPONSE PARAMETERS
3.6.1 MEAN ARITHMETIC ROUGHNESS
Surface roughness is a measure of the texture of a surface. It is quantified by the vertical deviations of a real surface from its ideal form. If these deviations are large, the surface is rough; if they are small the surface is smooth. Roughness is typically considered to be the high frequency, short wavelength component of a measured surface.
Roughness plays an important role in determining how a real object will interact with its environment, as rough surfaces usually wear more quickly and have higher friction coefficients than smooth surfaces. Roughness is often a good predictor of a mechanical component. Irregularities in the surface may form nucleation sites for cracks or corrosion. Also, it may promote adhesion. Roughness is typically measured in "RMS" micro-inches and is often only measured by manual comparison against a "surface roughness comparator", a sample of known surface roughness.
There are many different roughness parameters in use, but R a is by far the most common. Ra is the arithmetic average of the absolute values and R a is the arithmetic average of the absolute values. 1 R a is typically expressed in "millionths" of an inch. This is also referred to as micro inches or sometimes just as "micro"
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3.6.2 TOOL TEMPERATURE
Temperature is a physical quantity that is a measure of hotness and coldness on a numerical scale. It is a measure of the thermal energy per particle of matter or radiation; it is measured by a thermocouple in Celsius. Tool life is primarily affected by a high temperature in thin surfaces subjected to wear.
3.6.3 TOOL WEAR
Tool wear describes the gradual failure of cutting tools due to regular operation. Types of wear include:
1. FLANK WEAR
Flank wear is attributed usually to the following reasons:
1. Abrasion by hard particles and inclusions in the workpiece.
2. Shearing of the micro-welds between tool and work material.
3. Abrasion by fragments of built up edge blowing against the clearance face of the tool. 2. CRATER WEAR
In which contact with chips erodes the rake face. This is somewhat normal for tool wear, and does not seriously degrade the use of a tool until it becomes serious enough to cause a cutting edge failure It can be caused by spindle speed that is too low or a feed rate that is too high. In orthogonal cutting this typically occurs where the tool temperature is highest. Crater wear occurs approximately at a height equaling the cutting depth of the material.
EFFECTS OF TOOL WEAR
• increased cutting forces
• increased cutting temperatures
• poor surface finish
• decreased accuracy of finished part
Reduction in tool wear can be accomplished by using lubricants and coolants while machining. These reduce friction and temperatures, thus reducing the tool wear.
3.7 TOOL PREPARATION
M-42 HSS bit tools have been prepared in IGTR Indore of dimensions - 3/8''x3/8''x1.5'' (Inches). A 01 mm precision hole upto a distance of 2 mm from the tool tip was also made by the method of Wire Cut EDM (Electric Discharge Machine). Total 9 tools are prepared of different rake angles and tool radius for performing 9 sets of experiments in each dry and wet environment.
3.8 DESIGN OF EXPERIMENTS
Since the project work involves 4 machining parameters with 3 levels, therefore the number of experiments comes out to be 81 as per full factorial design. To minimize the number of experiments, Taguchi’s technique of DOE was applied and using L9 orthogonal array of Taguchi, the number of experiments was reduced to 9. A Taguchi design, or an orthogonal array, is a method of designing experiments that usually requires only a fraction of the full factorial combinations. An orthogonal array means the design is balanced so that factor levels are weighted equally, Because of this, each factor can be evaluated independently of all the other factors, so the effect of one factor does not influence the estimation of another factor. The advantage of Taguchi technique is that while reducing the number of experiments, it not only accounts for the individual effect of parameters but also considers the interaction effect of all the parameters. Designed experiments are often carried out in four phases: planning, screening, optimization, and verification. The Table 3.4 of L9 orthogonal array was generated with the help of Minitab (Version 16) Software.
TABLE 3.4 Experiment design by Taguchi L9 orthogonal array
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3.9 CONDUCTION OF EXPERIMENT
The most influential factors affecting the surface finish and tool wear were studied by conducting a set of experiments. The size of the sample workpiece was selected after a number of multiple experiments performed on single test workpiece, thus due to problem of vibration and self-weight of rod, the sample size as length 15 cm and diameter 22 mm were selected.
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Figure 3.5 Picture showing Scheme of Experiment and Analysis
Also time of experiment was selected as 40 secs for each set in order to achieve a steady state condition for temperature. It was selected by performing test runs and observing visually and then 10 secs were added to the time observed. Thus the time for experiment was selected.
3.10 ARRANGEMENT FOR TEMPERATURE MEASUREMENT
Figure 3.5 shows the arrangement for temperature measurement. In the figure thermocouple is the temperature measuring unit which senses the environmental temperature and produces an output what is shown to us and recorded visually.
A thermocouple consists of two dissimilar conductors in contact, which produces a voltage when heated. The size of the voltage is dependent on the difference of temperature of the junction to other parts of the circuit. Thermocouples are a widely used type of temperature sensor for measurement and control and can also be used to convert a temperature gradient into electricity.
Any junction of dissimilar metals will produce an electric potential related to temperature. Thermocouples for practical measurement of temperature are junctions of specific alloys which have a predictable and repeatable relationship between temperature and voltage. Different alloys are used for different temperature ranges. Electronic instruments can also compensate for the varying characteristics of the thermocouple, and so improve the precision and accuracy of measurements.
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Figure 3.6 Arrangement for temperature measurement
SPECIFICATIONS
• SUPPLY 90-270 VAC/DC
• FREQUENCY 50/60 Hz
The thermocouple wire was inserted in the precision hole of hole and power supply is switched on, thus as the experiment goes on, the thermocouple senses the temperature produced in the tool due to heat generation and gives as output on display.
The thermocouple wire was inserted in the precision hole of hole and power supply is switched on, thus as the experiment goes on, the thermocouple senses the temperature produced in the tool due to heat generation and gives as output on display.
3.11 ARRANGEMENT FOR SOLID LUBRICANT FEEDING
This is the arrangement showing the boric acid powder feeder.
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Figure 3.7 Schematic diagram of the setup for the solid lubricant feeding
3.11.1 EXPERIMENTAL SETUP FOR SOLID LUBRICANT FEEDING
The primary objective of the solid lubricant powder feeder setup is to maintain constant flow rate of powder to the machining zone in order to attain optimum results in machining. The designed experimental set up together with the solid lubricant powder feeder system is shown in Figure 3.7 The solid lubricant powder feeder system is comprised of five components: the solid lubricant feeder, shaft, helical blades, the single phase induction motor, and the casing. The cylindrical portion of the feeder is clamped to the support and welded with the upper and lower conical portions; it is called a solid lubricant feeder. The single-phase stepper motor is mounted on a platform. It supports and rotates the shaft to which the helical blades are welded around the periphery. The portion of the shaft containing helical blades is placed inside the cylindrical portion of the solid lubricant feeder. The solid lubricant is supplied into the machining zone as the feeder moves along the length of the shaft, which is being turned. The solid lubricant feeder together with the motor is mounted on the carriage, in order to facilitate the movement of feeder system with tool during machining operation.
WORKING PRINCIPLE
The fine solid lubricant powder, with 2 pm average particle size, was loaded into the upper conical part (hopper) of the feeder. The powder falls into the cylindrical portion of the feeder due to gravity. It is then pushed out of the cylindrical portion with the help of the blades placed around the periphery of the motor-driven shaft. The powder, pushing out through the cylindrical part, was transferred first to the lower conical portion and then to the machining zone. The opening at the end of the lower conical portion is selected in such a way that it is just sufficient for the powder to flow continuously onto the workpiece. Further, the cutting action of the tool and workpiece will drag the powder to the machining zone. After ensuring the setup for proper lubrication, the experiments were carried out. The entire machining operation, while using solid lubricant, was carried out in a closed chamber. Thus, powder is not allowed to mix freely in air. Trial experiments were carried out to see the influence of increasing flow rate of solid lubricant powder from 1 gm/s to 12 gm/s on the friction coefficient. It could be seen from the experimental results that the saturation of powder flow rate was observed at 5 gm/s, hence, all the experiments in boric acid powder assisted machining were carried out at 5 gm/s flow rate.
3.12 MEASUREMENT OF RESPONSE PARAMETERS
3.12.1 TEMPERATURE
The Temperature measurement during turning is a complex process which was measured successfully because of precision hole on the tool tip. Temperature was measured with the help of a of digital display type thermocouple, which is explained earlier in section 3.6.
3.12.2 ROUGHNESS
Surface Roughness measurement is done with the help of Taylor Hobson Precision Surface Roughness Testing Machine with the courtesy of IIT Delhi. The roughness measurement for dry and wet conditions has been done separately and then a comparative study of the surface finish obtained by two arrangements is done. A number of 3 roughness measures were performed on a single sample and then the average value of 3 measurements is taken as average surface roughness value.
TAYLOR HOBSON PRECISION SURFACE ROUGHNESS TESTING MACHINE
Taylor Hobson is a high precision technology company, operating at the highest levels of accuracy within the field of surface, roundness and form measurement. Composite granite and welded steel construction provide stiffness and stability throughout the measuring loop, while a pneumatic anti-vibration system isolates the instrument from external vibrations. Simple set-up and operation. Measurement set-up is easy: place the component on the positioning stage, set the focus height, and push the start button; components need only be free of contamination. Unusual samples can be measured by using a combination of stitching, auto focus, fixtures, jigs and vacuum chucks. Artifacts traceable to international standards are used to calibrate the instrument in both the vertical and lateral measurement axes. Therefore, the geometrical, dimensional and surface characteristics of any artifact can be easily reproduced with confidence. Specimen areas larger than the maximum 7mm x 7mm field of view can be measured using the data stitching feature. The stitching feature can also be used to take very high-resolution measurements over areas up to the maximum size of the automated X-Y-Z stage used.
TABLE 3.5 Specification of Taylor Hobson Precision Surface Roughness Testing Machine
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Figure 3.8 Picture showing roughness values for dry and wet turning measured by Taylor Hobson Precision Surface Roughness Testing Machine
3.12.3 TOOL WEAR
Flank Wear Measurement has been performed using a Measuring Microscope Model No.
AT112-50F.
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Figure 3.9 Picture showing measurement of Flank Wear in Tool
3.13 CHIP MORPHOLOGY
3.13.1 CHIP MORPHOLOGY DEFINITION AND TYPES
Chip morphology is the study of the pattern of chips obtained after turning of workpiece under different set of parameter and environmental conditions. Chips produced in machining most metals and alloys can be generally classified into four distinct categories based on their geometric shapes: Flow, Wavy, saw-toothed Segmented, and Discontinuous.
Flow type chip arises in machining of ductile materials and is classified by its uniform cross-section. Wavy chips occur when the shear angle oscillates widely causing fluctuations in cutting forces and chip thickness. When there are cracks or fracture in the chip formation, the Chip may be discontinuous or saw-toothed Segmented. Discontinuous chip Formation is common in machining brittle materials at low cutting speeds. Saw-toothed chips, a common name for segmented chips, are semi continuous and have zones of low shear Strain (continuous portion) and high shear strain (discontinuous portion). Saw-toothed chips, unlike conventional flow type or continuous chips, show areas of intense shear strain in cyclic form causing sharp segments.
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Figure 3.10 Picture showing chip morphology for different experiment sets under dry and wet environment
3.13.2 CHIPS OBTAINED IN SOLID LUBRICANT AND WET TURNING
The chip and shape of chip obtained in solid and liquid lubricant assisted turning has been summarized in Table 3.6.
Table 3.6 Size and Shape of chips obtained in experiments
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CHAPTER 4
OBSERVATION ANALYSIS & DISCUSSION
4.1 DESCRIPTION OF SOFTWARE TOOLS
Minitab® 16.2.3 is used for the purpose of analysis. The software package helped in the following:
1. Design of experiment
2. To plot Main Effect plots for mean
3. To plot S/N Ratio curves
4. To find the optimum parameters
5. To conduct Regression Analysis
6. To perform an ANOVA Test
Microsoft Office Excel 2007 is used to plot various response parameters on a single graph for comparison purposes.
4.2 OBSERVATION TABLE:
Nine set of experiments was conducted for both Solid Lubricant-assisted Machining and Liquid Lubricant. For each set of experiments, Tool Temperature and Roughness were measured. The Test results are summarized in the table 4.1 and 4.2.
Table 4.1 Output Record in the presence of liquid lubricant
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Table 4.2 summarizes the output response of various test runs obtained when boric acid powder was used as lubricant.
Table 4.2 Output Record in presence of Boric Acid
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In addition to the above the Flank Wear of different tools used in the experiment was also measured. The Flank Wear Width with Tool Geometries has been summarized in Table 4.3. The tools are taken in order of experiment conducted.
Table 4.3 Flank Wear width of various tools
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4.3 GENERAL LINEAR REGRESSION MODEL
General regression investigates and models the relationship between a response (Y) and input(s) (X). The response must be continuous. We can model both linear and polynomial relationships using general regression.
In particular, regression analysis is often used to:
• determine how the response variable changes as a particular predictor variable changes • predict the value of the response variable for any value of the predictor variable, or combination of values of the predictor variables
In the current study, the relationship between the input(X), called the cutting conditions (feed rate f), cutting speed (V c), Nose Radius (r) and Rake Angle (a) of the tool) and the response Y that is output (Mean Arithmetic Roughness (R a), Tool Temperature (T) and Tool Wear (W)) is given as:
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Where $ is a response function. The approximation of Y is proposed using following linear regression equation because of its simplicity and powerful prediction of results as available in literature.
The quadratic model for the response variable Y can be written as:
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Where Y is the outcome, x , (1, 2,....., k) denotes the independent quantitative process factors, fi o denotes the intercept, and fi i fi i i, and fi ij denote the corresponding linear, quadratic, and interaction coefficients.
Where
a0 = is the constant
b [ = coefficient of independent terms b [j = coefficient of interacting terms X [ = input parameters (feed rate (f), cutting speed (V c), Nose Radius(r) and Rake Angle(a) of the tool)
Y = Response parameters (Mean Arithmetic Roughness (R a), Temperature (T) and Tool Wear (W))
The application of standard statistical procedure will develop an equation which can predict the response parameter in terms of input parameter. Following are the linear regression equation as predicted by MINITAB-16:
4.3.1 Regression equation for Mean Arithmetic Roughness[21]
The mean average roughness can be predicted by following linear equation:
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4.3.2 Regression equation for Temperature
The mean average temperature can be predicted by following linear equation:
(7) soiid = 33.5016 + 99.8244 f + 0.101655 V c - 52.8259 r - 0.0254645 a -1.86823 fx V c + 143.571 fx r + 0.457455 V cXr
(7) iiquid = 17.3743 - 79.9727 f - 0.186776 V c - 12.4863 r + 0.253443 a - 0.60765 f x V c + 30 f x r +0.125137 V cx r
4.3.3 Regression equation for Tool Wear
The flank wear can be predicted by following linear equation:
W = -0.0376419 + 0.762253 f + 0.00190127 V c - 0.00444477 r - 0.00232508 a- 0.00588812 f x V c -0.286429 f x r + 0.0004821 V c x r
Where
R a = Mean Arithmetic Roughness in pm
T = Temperature in oC
W = Flank wear width in pm
f = Feed rate in mm/rev
V c = Cutting speed m/min
r = Nose radius in mm
a = Rake Angle in degree
4.4 STATISTICAL ANALYSIS BY ANOVA (ANALYSIS OF VARIANCE)
Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences between group means and their associated procedures. ANOVAs are useful in comparing (testing) means of groups or variables for statistical significance.
A variance analysis of the surface roughness (R a) and the Tool Temperature (T), was made with the objective of analysing the influence of feed rate, cutting speed, nose radius and rake angle on the results.
The ANOVA Table (Analysis of Variance) table gives the following information:
1. Degrees of Freedom
2. The Sum of the Squares
3. The Mean Square
4. The F ratio
5. The p-value
The most important statistic in the analysis of variance table is the p-value (P). There is a p-value for each term in the model (except for the error term). The p-value for a term tells you whether the effect for that term is significant:
• If p is less than or equal to the a-level(Level of Significance) selected, then the effect for the term is significant.
• If p is larger than the a-level selected, the effect is not significant.
S, R and adjusted R are measures of how well the model fits the data. These values can help you select the model with the best fit. The best model is that which have a adjusted R value close to 1.
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Calculation of degree of freedom:
DF for total = DF for all factors + DF for all interactions + DF for error.
DF total = n - 1 where n is the total number of observations.
DF for factor = k - 1 where k is the number of the factor levels.
DF for Interaction = (k1 - 1) x (k2 -1) where k1 is the number of levels of factor one, and k2 is the number of levels of factor two. The same rule applies to interactions of more than two factors.
4.4.1 ANOVA RESULT FOR ROUGHNESS
4.4.1.1 The ANOVA at 95.0% level of confidence when applied for the roughness with Solid Lubricant Assisted Machining (Boric Acid Powder) following table has been formed.
Table 4.4 ANOVA Result for Roughness with Solid Lubricant at a=0.05
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Summary of Model
S = 0.496794
R-Sq = 96.63%
R-Sq (adj) = 93.26%
R-Sq (pred) = 85.16%
The abbreviations used in the above table are:
DoF - Degree of Freedom
Seq SS - sequential sums of squares
Adj SS - adjusted sums of squares
Adj MS - adjusted mean squares
4.4.1.2 The ANOVA at 95.0% level of confidence when applied for the roughness with liquid lubricant following table has been formed.
Table 4.5 ANOVA Result for Roughness with liquid lubricant at a=0.05
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Summary of the Model:
S = 0.348569
R-Sq = 98.67%
R-Sq(adj) = 97.33%
R-Sq(pred) = 94.25%
The R-Sq(adj) values for both the observation set were found very close to 1 (93.26% with solid lubricant and 97.33% with liquid lubricant). It means the regression equation provided in section 3.1 fits the model very well.
The analysis as given in table 4.4 and 4.5 clearly indicates that while turning the Al- 6061 bar feed is the significant parameter in both Solid and liquid lubricant assisted turning. It was also observed that Cutting Speed is a significant parameter in liquid lubricant assisted turning but no such significance was observed in solid lubricant assisted turning. The result were calculated at 95% level of confidence. It may possible that cutting speed will become a significant parameter at some lower level of confidence due to closeness of p value of cutting speed (0.058717) and a value (0.05).
4.4.1.3 Comparison of percentage contribution of input parameters on Roughness using different lubricant
The percentage contribution of various input parameter obtained in table 4.4 and 4.5 has been shown in figure 4.1.
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Figure 4.1 Contribution of Input Parameters on Surface Roughness
It can be observed from the table that feed shows highest contribution on surface roughness. It shows 57.57% contribution in case of liquid lubricant and 59.0% contribution in case of solid lubricant. The cutting velocity also contributes significantly on surface roughness showing 40.72% in case of liquid lubricant and 38.69% in case of solid lubricant. The nose radius and rake angle do not show any significant contribution on roughness.
4.4.2 ANOVA RESULT FOR TEMPERATURE
4.4.2.1 The ANOVA at 95.0% level of confidence when applied for the Tool Temperature with Solid Lubricant Assisted Machining (Boric Acid Powder) following table has been formed.
Table 4.6 ANOVA Result for Temperature with solid lubricant at a=0.05
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Summary of the Model:
S = 5.61455
R-Sq = 82.76%
R-Sq (adj) = 65.53%
4.4.2.2 The ANOVA at 95.0% level of confidence when applied for the Tool Temperature with liquid lubricant following table has been formed.
Table 4.7 ANOVA Result for Temperature with liquid lubricant at a=0.05
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Summary of Model
S = 0.527910
R-Sq = 86.07%
R-Sq (adj) = 72.13%
The R-Sq (adj) values for both the observation sets were found close to 1 (82.76% with solid lubricant and 86.07% with liquid lubricant). It means the regression equation provided in section 3.2 fits the model satisfactorily.
4.5 COMPARISON OF LUBRICANT PERFORMANCE ON
THE RESPONSE PARAMETERS
4.5.1 Effect on Surface Roughness:
Observed Surface Roughness in tables 4.1 and 4.2 are plotted in a graphical form for the purpose of comparison.
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Figure 4.2 Comparison of Surface Roughness
The comparative performance of Solid Lubricant assisted machining with the Liquid Lubricant machining can also be seen in Fig. 4.2. For each data set it can be observed that surface quality obtained using solid lubricant is much better than liquid lubricant. The lubricant effectiveness in minimizing the frictional effects at the tool and workpiece interface in the case of solid lubricant assisted turning is evident from the reduced surface roughness compared to that of cutting fluid assisted machining. Boric Acid is known to be good solid lubricant because of the low friction at the interface, which could have contributed to the reduction of surface roughness. The substantial reduction of surface roughness by boric acid assisted machining can be attributed to the formation of the thin film of lubrication, reducing the shear strength of material at the machining zone, so that machining becomes easier.
4.5.2 Effect on Tool Temperature:
Observed Tool temperature in table 4.1 and 4.2 are plotted in a graphical form for the purpose of comparison. The plot has been shown in figure 4.3.
For each data set it was found that the tool temperature with solid lubricant is low as compared to liquid lubricant. Similar reason can be applied here. The solid lubricant minimizes the frictional effect at tool work interface. The substantial reduction of cutting force by boric acid assisted machining can be attributed to the formation of the thin film of lubrication, reducing the shear strength of material at the machining zone, so that machining becomes easier. Hence lower temperature obtained in case of solid lubricant.
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Figure 4.3 Comparison of Tool Temperature
As expected the higher feed and cutting speed gives higher temperature and the lower cutting speed and feed give the lower temperature. This observation, that higher the cutting speed and feed higher the temperature has been demonstrated by many previous researchers
4.6 MAIN EFFECT PLOTS FOR MEAN
These plots are used in conjunction with an analysis of variance and design of experiments to examine differences among level means for one or more factors. A main effect is present when different levels of a factor affect the response differently. A main effects plot graphs the response mean for each factor level connected by a line.
General patterns to look for:
• When the line is horizontal (parallel to the x-axis), then there is no main effect present. Each level of the factor affects the response in the same way, and the response mean is the same across all factor levels.
• When the line is not horizontal, then there is a main effect present. Different levels of the factor affect the response differently. The steeper the slope of the line, the greater the magnitude of the main effect.
4.6.1 Main Effect plot for Roughness
The main effect plots generated from Minitab v16 software for roughness with Solid lubricant are shown in Figure 4.4. These plots reflect the variation of roughness with the input parameters parameters
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Figure 4.4 Main Effect Plot for Roughness with Solid Lubricant
The main effect plots generated from Minitab v16 software for roughness with liquid lubricant are shown in Figure 4.5. These plots reflect the variation of roughness with the input parameters
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Figure 4.5 Main Effect Plot for Roughness with liquid lubricant
From the main effect plot it can be observed that Roughness increases with increase in feed in both solid and liquid assisted machining. This is due to the fact that with increase in feed the undeformed chip thickness increases which results increased cutting force hence roughness increases.
The roughness decreases with increase in cutting velocity because Higher temperatures are generated while machining at higher cutting conditions, which results in reduction of the shear strength of the work material and hence, reduction in the cutting forces. Consequently, the surface finish is better. The effect of nose radius and rake angle is almost negligible as shown in the plot. The result can also be tested by the higher p-value for rake angle and nose radius in table 4.4 and 4.5.
4.6.2 Main Effect plot for Tool Temperature
The main effect plots generated from Minitab v16 software for temperature with solid lubricant and liquid lubricant are shown in fig. 4.6 and fig. 4.7. These plots reflect the variation of temperature with the input parameters
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Figure 4.6 Main Effect Plot for Temperature with Solid Lubricant
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Figure 4.7 Main Effect Plot for Temperature with liquid lubricant
The analysis of above two graph shows that with an increase in feed the temperature increases. This is due to the fact that the amount of heat generation increases with increase in feed rate, because the cutting tool has to remove more volume of material from the work piece. The temperature also increases with increase in cutting speed. At high cutting speed higher temperature has been observed since less heat was dissipated to the work material and more heat is transferred through tool.
The increase in nose radius contributes in higher temperature because more force generated due to inefficient cutting which result in high temperature. The temperature was found to increase with rake angle upto some limit and decreases afterwards in both solid and liquid lubricant-assisted machining.
4.7 OPTIMIZATION OF PARAMETERS USING S/N RATIO
In Taguchi designs, a measure of robustness used to identify control factors that reduce variability in a product or process by minimizing the effects of uncontrollable factors (noise factors). Control factors are those design and process parameters that can be controlled. Noise factors cannot be controlled during production or product use, but can be controlled during experimentation. In a Taguchi designed experiment, noise factors are manipulated to force variability to occur and from the results, identify optimal control factor settings that make the process or product robust, or resistant to variation from the noise factors. Higher values of the signal-to-noise ratio (S/N) indicate control factor settings that minimize the effects of the noise factors. Taguchi experiments often use a 2-step optimization process. In step 1 use the S/N ratio to identify those control factors that reduce variability. In step 2, identify control factors that bring the mean to target and have little or no effect on the S/N ratio. The signal-to-noise (S/N) ratio measures how the response varies relative to the nominal or target value under different noise conditions. In S/N ratio analysis, ‘Larger is better’ strategy is used when the response is to be maximized and ’Smaller is better’ strategy is used when the response is to be minimized. The formulas used to calculate the S/N ratios for both the strategies are listed in Table 4.8.
Table 4.8 S/N ratios for different strategies
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4.7.1 S/N Ratio Plots for Roughness
For selection of significant parameters that influence roughness, the ‘smaller the better strategy’ is applied and the S/N ratio plots are obtained as shown in figure 4.8 and fig 4.9. These plots were generated using Minitab v16 software.
4.7.1.1 S/N Ratio plot for Solid Lubricant assisted turning
S/N ratio plot for roughness with solid lubricant has been shown in fig. 4.8.
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Figure 4.8 S/N ratio for Roughness in Solid Lubricant assisted turning
By using the ‘Smaller is Better strategy’ the optimum parameters are-
Feed = 0.3 mm/rev
Cutting Speed = 75m/min
Nose Radius = 1.2mm
Rake Angle = 10°
4.7.1.2 S/N Ratio plot for Liquid Lubricant assisted turning
S/N ratio plot for roughness with liquid lubricant has been shown in fig. 4.9
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Figure 4.9 S/N ratio for Roughness in Liquid Lubricant-assisted turning
By using the ‘Smaller is Better strategy’ the optimum parameters are-
Feed = 0.3 mm/rev
Cutting Speed = 75m/min
Nose Radius = 1.2mm
Rake Angle = 10°
The comparison of above two plots reveals that the optimum parameters for roughness are same in both solid and lubricant assisted turning.
4.7.2 S/N Ratio Plots for Temperature
For selection of significant parameters that influence roughness, ‘smaller the better strategy’ is applied and the S/N ratio plots are obtained as shown in Figure 4.10 and 4.11. These plots were generated using Minitab v16 software.
4.7.2.1 S/N Ratio plot for Solid Lubricant assisted turning
S/N ratio plot for temperature with solid lubricant has been shown in fig. 4.10
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Figure 4.10 S/N ratio for Temperature in Solid Lubricant assisted turning
4.7.2.2 S/N Ratio plot for Solid Lubricant assisted turning
S/N ratio plot for temperature with liquid lubricant has been shown in fig. 4.11.
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Figure 4.11 S/N ratio for Temperature in Liquid Lubricant assisted turning
By using the ‘Smaller is Better strategy’ the optimum parameters obtained from fig 4.9 and Fig. 4 .10 are-
Feed = 0.3 mm/rev
Cutting Speed = 30m/min
Nose Radius = 1.2mm
Rake Angle = 10° (in case of solid lubricant) and 5°(in case of liquid lubricant)
The comparison of the above two plots reveals that the optimum parameters for roughness are the same in both solid and lubricant-assisted turning, except for the rake angle.
4.8. ANALYSIS OF TOOL WEAR
4.8.1 Statistical Analysis by ANOVA
The ANOVA at 95.0% level of confidence when applied for tool wear following table 4.9 has been formed:
Table 4.9 ANOVA Result for Tool Wear at a=0.05
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Summary of Model
S = 0.496794
R-Sq = 92.09%
R-Sq(adj) = 84.18%
The R-Sq(adj) values for the analysis was found close to 1 (84.18%). It means the regression equation provided in section 3.3 fits the model satisfactorily.
4.8.2 Percentage contribution of various parameters in Tool Wear
The percentage contribution of the input parameter obtained in Table 4.9 is shown in Figure 4.12.
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Figure 4.12 Percentage contribution of various parameters in tool wear
It can be observed that cutting speed shows largest contribution in tool wear (64.89) similar results has been reported by past researchers. The feed also contributes significantly in tool wear showing 30.15%. The effect of nose radius on tool wear is very low as shown in the graph. The rake angle shows negligible contribution on tool wear as shown in above figure.
4.8.3 Main Effect Plot for Tool Wear
General patterns to look for:
• When the line is horizontal (parallel to the x-axis), then there is no main effect present. Each level of the factor affects the response in the same way, and the response mean is the same across all factor levels.
• When the line is not horizontal, then there is a main effect present. Different levels of the factor affect the response differently. The steeper the slope of the line, the greater the magnitude of the main effect.
The main effect plot for tool wear has been shown in figure 4.13
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Figure 4.13 Main effect plot for Tool Wear
It can be observed that the cutting speed has the highest influence followed by feed rate from the figure. It is clear that tool wear increases with increase in feed. The increased speed significantly increases the temperature at the contact zone, which even exceeds the limits of the allowed thermal stability of the cutting material. Consequently, this leads to drastic increase of the tool wear.
With the increase in cutting speed, the rubbing action between tool and work piece is faster and more heat produced even though less contact time exits. The generation of heat at the flank side softens the tool edge and more wear occurred.
The nose radius and rake angle shows similar effect on tool wear it first decreases touches a least value and then increases. With an increase in rake angle, the tool tip becomes sharp which contributes in efficient cutting and less tool wear. But after a certain value the strength of tool tip decreases and wear increases. With increase in nose radius the contact area increases and also the cutting force which contributes in tool wear.
4.8.4 Optimization Using S/N Ratio
For selection of significant parameters that influence tool wear, ‘smaller the better strategy’ is applied and the S/N ratio plots are obtained as shown in Figure 4.14. These plots were generated using Minitab v16 software.
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Figure 4.14 S/N ratio plot for tool wear
By using the ‘Smaller is Better strategy’, the optimum parameters are-
Feed = 0.3 mm/rev
Cutting Speed = 75m/min
Nose Radius = 0.4mm
Rake Angle = 15°
Table 4.10 Optimum parameters for the responses
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4.9. ANALYSIS OF CHIP MORPHOLOGY
The sample of chips obtained in solid and liquid lubricant assisted turning has been shown in fig 4.15.
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Figure 4.15 Sample chips obtained (a) With Liquid Lubricant (b) With Solid Lubricant
From each observation set it was found that solid lubricant-assisted turning shows longer chip as compare to liquid assisted turning. It may be due to the fact that in liquid assisted turning alternative heating and cooling takes place due to machining condition and lubricant application. This may induce some brittle nature in chips so smaller chips observed in this case.
CHAPTER 5
CONCLUSION
Following conclusion can be drawn from the project:
1. Al-6061 can be used in a variety of application such as construction of aircraft structures such as wings and fuselage, automotive parts such as wheel spacers, in the manufacture of aluminium cans etc.
2. The numbers of experiments were reduced by L9 orthogonal array of Taguchi’s theory of design of experiments. The Taguchi technique was applied to study the individual effect as well as the interaction effect of the input parameters on the response parameter.
3. The input parameters were selected based on literature and trial experiment. These were feed, Cutting Speed, Nose Radius and Rake Angle.
4. Solid and liquid lubricants were selected for the purpose of comparison on response parameters.
5. The effect of input parameters was investigated on Surface Roughness, Tool Temperature and Tool Wear.
6. The effect of lubrication method was observed on chip morphology.
7. The ANOVA analysis indicates that feed is a significant parameter in solid lubricant assisted machining while feed and cutting speed both becomes significant in liquid assisted machining while evaluating roughness.
8. Percentage contribution of feed on roughness was found 59.0% and 57.57% while percentage contribution of cutting velocity on roughness was found 38.69% and 40.72% in solid and liquid lubricant assisted machining respectively. Nose radius and Rake angle show no significant effect on roughness.
9. The ANOVA analysis indicates that feed is a significant parameter in solid lubricant assisted machining as well as liquid assisted machining while evaluating Temperature.
10. Solid lubricant is more effective as compared to liquid lubricant while evaluating Roughness and Tool Temperature.
11. The influence of cutting velocity is maximum on tool wear (64.89%) followed by feed (30.15%). Nose radius and Rake angle shows no significant effect on tool wear.
12. The chip morphology is greatly influenced by the type of lubricant used. Smaller chips were obtained in case of liquid lubricant while larger and continuous chips were obtained with solid lubricant.
13. The numbers of experiments in the same or similar area in turning operations were reduced by using the Taguchi experimental design to determine optimum cutting conditions. Satisfying results were obtained so that they may be used in future academic and industrial studies.
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3. Byrne, G. and Scholta, E., Environmentally clean machining processes - a strategic approach. Ann. CIRP, 1993, 42(1), 471-474.
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- Sanjay Agarwal (Author), 2013, Experimental Investigation to Study the Effect of Solid Lubricant on Performance Characteristics in Turning Al-6061, Munich, GRIN Verlag, https://www.grin.com/document/1687249
