Hard Turning of Hot Work Tool Steel (Dac10)

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1 CHAPTER 1 1.1 HARD TURNING Hard Turning is a turning done on materials with Rockwell hardness greater than 45. Hard turning is a developing technology that offers many potential benefits compared to grinding, which remains the standard finishing process for critical hardened surfaces. To increase the implementation of this technology, questions about the ability of this process to produce surfaces that meet surface finish and integrity requirements must be answered. Additionally, the economics of the process must be justified, which requires a better understanding of tool wear patterns, life predictions, cause and effects of defects, also to formulate effective measures to counter the same. The ultimate aim of hard turning is to remove work piece material in a single cut rather than a lengthy grinding operation in order to reduce processing time, production cost, surface roughness, and setup time.Due to the potential advantages of the hard turning process, this research proposes to investigate the wear behavior of cutting tools in hard turning applications with the hope that findings will lead to further implementation in industry. The experimental work in combination with the development of a wear model based on the fundamental wear mechanisms typical in metal cutting will help to identify the effect of cutting parameters and tool material on wear behavior and tool life.

description

hard turning of hot work tool steel DAC10 with ceramic tool inserts

Transcript of Hard Turning of Hot Work Tool Steel (Dac10)

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CHAPTER 1

1.1 HARD TURNING

Hard Turning is a turning done on materials with Rockwell hardness greater than 45. Hard turning is a developing technology that offers many potential benefits compared to grinding, which remains the standard finishing process for critical hardened surfaces. To increase the implementation of this technology, questions about the ability of this process to produce surfaces that meet surface finish and integrity requirements must be answered. Additionally, the economics of the process must be justified, which requires a better understanding of tool wear patterns, life predictions, cause and effects of defects, also to formulate effective measures to counter the same.

The ultimate aim of hard turning is to remove work piece material in a single cut rather than a lengthy grinding operation in order to reduce processing time, production cost, surface roughness, and setup time.Due to the potential advantages of the hard turning process, this research proposes to investigate the wear behavior of cutting tools in hard turning applications with the hope that findings will lead to further implementation in industry. The experimental work in combination with the development of a wear model based on the fundamental wear mechanisms typical in metal cutting will help to identify the effect of cutting parameters and tool material on wear behavior and tool life.

Fig.1 Hard Turning

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Additionally, this research will utilize response to optimize the hard turning process and determine ideal process conditions. Because of the increasing demands imposed on high-performance materials and the disastrous costly results of component failures, the need for enhanced machining technology has gained significance and importance. Ceramics being one fastest growing high performance application material, manufacturing union has given immense response to provide newer technologies to cater the ever rising appetite for these materials.

Hard turning is very much a part specific process. It excels at cutting complex geometries that contain intricate arcs, angles, and blended radii. Instead of having to buy a form wheel for the grinder, you can program the lathe's single point much faster and cheaper. Hard turning also consumes about one-tenth of the energy per unit volume of metal removed than grinding and is more environmental friendly.

1.2 BENEFITS FROM HARD TURNING

Smaller floor space requirement  " Soft turn" and hard turn on the same machine  Lower overall investment  Metal removal rates of 4-6 times greater  Can turn complex contours  Multiple operations in a single setup  Low micro finishes  Easier configuration changes  Lower cost tooling inventory  Higher metal removal rates  Easier waste management

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GRINDING VERSUS HARD TURNING

GRINDING HARD TURNING

1. Long set up times 2. Multiple clamping 3. Long cycle times 4. Low chip volume 5. Profiled grinding Wheel 6. Multiple dressing is non-productive 7. High investment cost 8. Environmental unfriendly due to grinding sludge

1. Short set-up times 2. Single clamping 3. Short cycle times4. High chip volume possible 5. Single point tool tip 6. More effective cutting time 7. Low investment cost 8. Dry cutting, clean process

1.3 APPLICATIONS

Shafts Sleeves Bearings Hydraulic components Bolts Punches Dies Transmission gears

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1.4 ADVANTAGES

The lathe offers the versatility to "Soft Turn" and Hard Turn on the same machine tool. A single machine performing the work of two has the added benefits of freeing up vital floor space and being a much lower capital investment.

Metal removal rates with hard turning are 4 to 6 times greater than equivalent grinding operations.

Single-point turning of complex contours is routine on a lathe, without the need for costly form wheels.

Multiple operations can be turned with a single set-up, resulting in less part handling and reduced opportunity for part damage.

Hard turning can achieve low micro-inch finishes. Surface finishes ranging from .0001 mm to .0004 mm are very common.

The hard turn lathe is generally more adaptable as configuration changes are introduced. Lathes are also able to process small batch sizes and complex shapes.

Environmentally, the hard turned chips are less costly to dispose of than grinding swarf. Dry cut parts without coolant contamination are even more economical to dispose of.

Tooling inventory is low compared to grinding wheels. Moreover, the CBN inserts will generally work in the existing tool holders used for multitudes of operation.

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Fig.2 Advantages of Hard Turning

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1.5 LITERATURE SURVEY

Optimization of turning parameters for surface roughness and tool life based on the Taguchi methodbyAhmet Hasçalık &Ulaş Çaydaş,

Department of Manufacturing, University of Firat, Turkey

In this study, the effect and optimization of machining parameters on surface roughness and tool life in a turning operation was investigated by using the Taguchi method.

The experimental studies were conducted under varying cutting speeds, feed rates, and depths of cut. An orthogonal array, the signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) were employed to the study the performance characteristics in the turning of commercial Ti-6Al-4V alloy using CNMG 120408-883 insertcutting tools.

The conclusions revealed that the feed rate and cutting speed were the most influential factors on the surface roughness and tool life, respectively. The surface roughness was chiefly related to the cutting speed, whereas the axial depth of cut had the greatest effect on tool life.

A surface roughness prediction model for hard turning process by Dilbag Singh, P. Venkateswara Rao, Mechanical Engineering Department, Indian Institute of Technology, Delhi

Experimental investigation was conducted to determine the effects of cutting conditions and tool geometry on the surface roughness in the finish hard turning of the bearing steel (AISI 52100). Mixed ceramic inserts made up of aluminum oxide and titanium carbon nitride (SNGA), having different nose radius and different effective rake angles, were used as the cutting tools.

This study shows that the feed is the dominant factor determining the surface finish followed by nose radius and cutting velocity. Though, the effect of the effective rake angle on the surface finish is less, the interaction effects of nose radius and effective rake angle are considerably significant.

The investigations of this study indicate that the parameters cutting velocity, feed, effective rake angle and nose radius are the primary influencing factors, which affect the surface finish. The results also indicate that feed is the dominant factor affecting the surface roughness, followed by the nose radius, cutting velocity and effective rake angle. First order surface roughness prediction model has been found to represent the hard turning process very well.

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Surface roughness modelling in hard turning operation of AISI 4140 using CBN cutting toolBy

Saeed Zare Chavoshi, Mehdi Tajdari

The influence of hardness (H) and spindle speed (N) on surface roughness (Ra) in hard turning

operation of AISI 4140 using CBN cutting tool was studied.

A multiple regression analysis using analysis of variance is conducted to determine the

performance of experimental values and to show the effect of hardness and spindle speed on the

surface roughness

The results show that hard ness has a significant effect on surface roughness. With the increase

of hardness until 55HRC the surface roughness decreases. spindle speed range of 2500-3000 has

a partial effect on surface roughness.

Wear Analysis Of Ceramic Cutting Tools In Finish Turning Of Inconel 718 ByM. Aruna, Dr. V. Dhanalakshmi, S. Mohan, Central Electrochemistry Research Institute, Cecri, Karaikudi

The approach is based on taguchi’s method and the analysis of variance (ANOVA). A series of experiments are conducted by varying theprocess parameters and their effects on surface finish and tool wear are measured. It is found that the surfaceroughness is well below the rejection criteria. The experimental results indicate that the cutting speed is the mostsignificant factor to the overall performance.

It is found from the results that less tool wear and good surface finish are obtained using ceramic tool when finish turning Inconel 718 at low speeds. The optimal cutting condition for good surface finish is 100 m/min and 0.1 mm/rev.

The tool failure occurs at a speed of 200m/min and a feed rate of 0.15 mm/rev. Finally, it is

concluded that the performance of ceramic tool is better at low cutting speeds. With the alumina

based ceramic insert, low surface roughness values are achieved.

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CHAPTER 2

2.1 SELECTION OF MATERIAL

Chromium-Molybdenum-Vanadium Hot work tool steel is selected for carrying out for this experimental work.

Material Selected: DAC10 (Japanese industrial Standards)

SPECIFICATIONS

Diameter: 55 mm, Length: 200 mm. 2 No’s.

Fig.3 Raw Work Piece Material

2.2 HOT WORK TOOL STEEL

The significance of tool steels extends far beyond what is generally perceived as common place. Nearly all the objects we are surrounded by and encounter on a daily basis are manufactured with the help of tool steels.H-grade tool steels were developed for strength and hardness during prolonged exposure to elevated temperatures. All of these tool steels use a substantial amount of carbide forming alloys. H1 to H19 are based on a chromium content of 5%; H20 to H39 are based on a tungsten content of 9%-18% and a chromium content of 3%–4%; H40 to H59 are molybdenum based.

Hot-work tool steel products are mainly exposed to high temperatures exceeding 200 °C. Since micro structural tolerances are minimal, the microstructure of these steels has to be sufficiently stable and resistant to tempering. Tools made from hot-work tool steels are not only subject to constantly high temperatures when employed, but also to fluctuating thermic loads occurring where the tool surfaces come into contact with the materials to be processed. Combined with the wear caused by abrasion or impact, these thermic loads constitute very specific requirements on

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the hot-work tool steels. Key demands are high tempering resistance temperature strength, thermal shock resistance, high-temperature, toughness and wear resistance.

2.3 APPLICATION

Steel for precision die casting and hot-working press die which has excellent heat crack resistance and wear resistance.

1. Die casting dies,2. Extrusion dies.

The application spectrum for hot-work tool steels is extensive and the tools manufactured are used in the most diverse areas. These steels enable the hot forming of work pieces made of iron and non-ferrous metals as well as alloy derivatives at high temperatures. They are utilized in processes such as pressure die casting, extrusion and drop forging as well as in tube and glass manufacturing.

2.4 COMPOSITION REPORT

ELEMENTS TESTED VALUES (%)

CARBON 0.33

MANGANESE 0.62

SILICON 0.34

PHOSPHOROUS 0.007

SULPHUR 0.001

CHROMIUM 5.08

NICKEL 0.05

MOLYBDENUM 2.19

ALUMINIUM 0.01

COBALT 0.02

COPPER 0.02

NIOBIUM <0.01

VANADIUM 0.66

Table 1 Composition of Hot Work Tool Steel

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2.5 SIGNIFICANCE OF ELEMENTS

CARBON:

Carbon is the main hardening element in all steels. The strengthening effect of C in steel consists of solid solution strengthening and carbide dispersion strengthening. As the C content in steel increases, strength increases, but ductility and weld ability decreases.

MANGANESE:

Manganese (Mn) is present virtually in all steels in amounts of 0.30% or more. Manganese is beneficial to surface quality in all carbon ranges.

SILICON:

In heat-treated steels, Si is an important alloy element, and increases harden ability, wear resistance, elastic limit and yield strength, and scale resistance in heat-resistant steels.

CHROMIUM:

Chromium (Cr) is medium carbide former. Chromium increases hardenability, corrosion and oxidation resistance of steels, improves high-temperature strength and high-pressure hydrogenation properties, and enhances abrasion resistance in high-carbon grades.

NICKEL:

Nickel (Ni) is a non-carbide forming element in steels. Nickel raises hardenability. In combination with Ni, Cr and Mo, it produces greater hardenability, impact toughness, and fatigue resistance in Steels.

TUNGSTEN:

Tungsten (W) is strong carbide former.As the content of W increases in alloy steels, W forms very hard, abrasion-resistant carbides, and can induce secondary hardening during the tempering of quenched steels.

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CHAPTER 3

3.1 CUTTING TOOLS

Cutting tool materials must have certain properties depending on the type of machining operations, work piece material being machined.

1. High hardness at elevated temperatures (hot hardness) to resist abrasive wear.

2. High deformation resistance to prevent the cutting edge from plastic deformation under high stresses and temperatures arising during chip formation.

3. High fracture toughness to resist edge micro-chipping and breakage especially in interrupted cutting.

4. Chemical inertness (low chemical affinity or high chemical stability) with respect to work piece material to protect against heat-affected wear types, i.e. Diffusion, chemical and oxidation wear.

5. High thermal conductivity to reduce temperatures near the cutting edge (the cool edge of the tool).

6. High fatigue resistance for tools suffering from peaked mechanical loads.

7. High thermal shock resistance which naturally follows the mechanical shock.

8. High stiffness required to maintain accuracy.

9. Adequate lubricant (low friction) to increase welding resistance and to prevent seizure (built-up edge formation).

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TOOL MATERIALS

TOOL MATERIAL

TYPICAL CUTTING SPEEDS, M/MIN

NOTES

Carbon Steel -Suitable only for soft materials as it starts to soften at temperatures of 230o C. Used for woodworking

High Speed Steels 10 - 60Very tough, two types, 'M' and 'T' with molybdenum and tungsten respectively as the main alloying element. Used for drills, reamers, taps and small end mills

Cast Cobalt - Chromium - Tungsten Alloys

-Not heat treatable, maximum hardness 55 - 65 Rc occurs near the surface. Can be used at somewhat higher speeds than HSS. Only in limited use

Cemented Carbides

30 - 150 or100 - 250 when coated

Originally produced in 1920s, these consisted of tungsten carbide (WC) in a cobalt binder. A useful feature is that they can be tailored to give different combinations of abrasion resistance and toughness by varying the amount of cobalt and the WC grain size. Other additions, such as TiC and TaC are frequently made. Coatings, such as AL2

Cermets 150 - 350A cermet is a composite of a ceramic material with a metallic binder. For machining titanium carbonitride based materials are used. Other carbides such as Mo2

Ceramics 150 - 650

Two classes are used for cutting tools: Al2O3 and silicon nitride (Si3N4). They are more stable than carbide tools at high temperatures, but are less fracture resistant, operate best at light loads and high speeds. May be made by sintering / hot pressing. ZrO2 may be added to improve fracture toughness but this reduces thermal conductivity and hardness. SiC whiskers may be added to give better toughness and improved thermal shock resistance

Cubic Boron Nitride

30 – 310Second in hardness to diamond. Standard choice for machining steel with a hardness of 50 Rc or higher

Polycrystalline Diamond

200 – 2000

Can not be used for machining steels as this causes graphitisation of the diamond. Used mainly for very high speed machining of aluminium silicon alloys, composites and other non - metallic materials

Table 2 Tool Materials

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Fig.4 Types of Cutting Tools

TYPES OF TOOL STEELS

1 Carbon Steels Carbon steels have been used since the 1880s for cutting tools. However carbon steels start to soften at a temperature of about 180oC. This limitation means that such tools are rarely used for metal cutting operations. Plain carbon steel tools, containing about 0.9% carbon and about 1% manganese, hardened to about 62 Rc, are widely used for woodworking and they can be used in a router to machine aluminum sheet up to about 3mm thick.

2 High Speed Steel (HSS) HSS tools are so named because they were developed to cut at higher speeds. Developed around 1900 HSS are the most highly alloyed tool steels. The tungsten (T series) were developed first and typically contain 12 - 18% tungsten, plus about 4% chromium and 1 - 5% vanadium. Most grades contain about 0.5% molybdenum and most grades contain 4 - 12% cobalt.

It was soon discovered that molybdenum (smaller proportions)could be substituted for most of the tungsten resulting in a more economical formulation which had better abrasion resistance

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than the T series and undergoes less distortion during heat treatment. Consequently about 95% of all HSS tools are made from M series grades. These contain 5 - 10% molybdenum, 1.5 - 10% tungsten, 1 - 4% vanadium, 4% Chromium and many grades contain 5 - 10% cobalt.

HSS tools are tough and suitable for interrupted cutting and are used to manufacture tools of complex shape such as drills, reamers, taps, dies and gear cutters. Tools may also be coated to improve wear resistance. HSS accounts for the largest tonnage of tool materials currently used. Typical cutting speeds: 10 - 60 m/min.

3 Cast Cobalt Alloys Introduced in early 1900s these alloys have compositions of about 40 - 55% cobalt, 30% chromium and 10 - 20% tungsten and are not heat treatable. Maximum hardness values of 55 - 64 Rc. They have good wear resistance but are not as tough as HSS but can be used at somewhat higher speeds than HSS. Now only in limited use.

4 Carbides Also known as cemented carbides or sintered carbides were introduced in the 1930s and have high hardness over a wide range of temperatures, high thermal conductivity, high Young's modulus making them effective tool and die materials for a range of applications. The two groups used for machining are tungsten carbide and titanium carbide, both types may be coated or uncoated. Tungsten carbide particles (1 to 5 micro-m) are bonded together in a cobalt matrix using powder metallurgy. The powder is pressed and sintered to the required insert shape. titanium and niobium carbides may also be included to impart special properties. A wide range of grades are available for different applications. Sintered carbide tips are the dominant type of material used in metal cutting. The proportion of cobalt (the usual matrix material) present has a significant effect on the properties of carbide tools. 3 - 6% matrix of cobalt gives greater hardness while 6 - 15% matrix of cobalt gives a greater toughness while decreasing the hardness, wear resistance and strength. Tungsten carbide tools are commonly used for machining steels, cast irons and abrasive non-ferrous materials. Titanium carbide has a higher wear resistance than tungsten but is not as tough. With a nickel-molybdenum alloy as the matrix, TiC is suitable for machining at higher speeds than those which can be used for tungsten carbide. Typical cutting speeds are: 30 - 150 m/min or 100 - 250 when coated.

5 Coatings Coatings are frequently applied to carbide tool tips to improve tool life or to enable higher cutting speeds. Coated tips typically have lives 10 times greater than uncoated tips. Common coating materials include titanium nitride, titanium carbide and aluminum oxide, usually 2 - 15 micro-m thick. Often several different layers may be applied, one on top of another, depending upon the intended application of the tip. The techniques used for applying coatings include chemical vapour deposition (CVD) plasma assisted CVD and physical vapour deposition (PVD). Diamond coatings are also in use and being further developed.

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6 Cermets Developed in the 1960s, these typically contain 70% aluminum oxide and 30% titanium carbide. Some formulation contains molybdenum carbide, niobium carbide and tantalum carbide. Their performance is between those of carbides and ceramics and coatings seem to offer few benefits. Typical cutting speeds: 150 - 350 m/min.

7 Ceramics

Alumina Introduced in the early 1950s, two classes are used for cutting tools: fine grained high purity aluminum oxide (Al2O3) and silicon nitride (Si3N4) are pressed into insert tip shapes and sintered at high temperatures. Additions of titanium carbide and zirconium oxide (ZrO2) may be made to improve properties. But while ZrO2 improves the fracture toughness, it reduces the hardness and thermal conductivity. Silicon carbide (SiC) whiskers may be added to give better toughness and improved thermal shock resistance. The tips have high abrasion resistance and hot hardness and their superior chemical stability compared to HSS and carbides means they are less likely to adhere to the metals during cutting and consequently have a lower tendency to form a built up edge. Their main weakness is low toughness and negative rake angles are often used to avoid chipping due to their low tensile strengths. Stiff machine tools and work set ups should be used when machining with ceramic tips as otherwise vibration is likely to lead to premature failure of the tip. Typical cutting speeds: 150 - 650 m/min. 

Silicon Nitride In the 1970s a tool material based on silicon nitride was developed, these may also contain aluminum oxide, yttrium oxide and titanium carbide. SiN has an affinity for iron and is not suitable for machining steels. A specific type is 'Sialon', containing the elements: silicon, aluminum, oxygen and nitrogen. This has higher thermal shock resistance than silicon nitride and is recommended for machining cast irons and nickel based super alloys at intermediate cutting speeds.

8 Cubic Boron Nitride (CBN) Introduced in the early 1960s, this is the second hardest material available after diamond. CBN tools may be used either in the form of small solid tips or or as a 0.5 to 1 mm thick layer of of polycrystalline boron nitride sintered onto a carbide substrate under pressure. In the latter case the carbide provides shock resistance and the CBN layer provides very high wear resistance and cutting edge strength. Cubic boron nitride is the standard choice for machining alloy and tool steels with a hardness of 50 Rc or higher. Typical cutting speeds: 30 - 310 m/min.

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3.2 SELECTION OF INSERTS

Ceramic cutting tools are harder and more heat-resistant than carbides, but more brittle. They are well suited for machining cast iron, hard steels, and the super alloys. Two types of ceramic cutting tools are available: the alumina-based and the silicon nitride-based ceramics. The alumina-based ceramics are used for high speed semi- and final-finishing of ferrous and some non-ferrous materials. The silicon nitride-based ceramics are generally used for rougher and heavier works.

KEY BENEFITS:

Excellent wear resistance and long tool life Stability over a wide variety of machining applications Produces excellent surface finishes

APPLICATIONS:

General turning and boring of gray cast iron Rough and finished cylinder liner materials Tube scarfing

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3.3 CERAMIC TOOL INSERT AB2010

Physical vapour deposited TiN coated AB2010 is a mixed ceramic grade of alumina oxide with an addition of titanium carbide nitride. The yellow coating makes it easy for operators and users to identify used/worn corners after machining a work piece. The application of this grade is finishing operations of hard steels and cast irons.

Fig.5 Ceramic Tool Inserts AB2010

3.4 SPECIFICATIONS OF TOOL INSERTS

For hardened steels of hardness 46-65 HRC the feed and cutting velocity ranges of this tool insert is 50-270 m/min and 0.05-0.2 mm/rev.

The inserts selected are:

DNGA 150604,

DNGA 150608,

DNGA 150612.

The cutting edge length is 15mm

Thickness of the tool 6mm

The nose radius is 0.8, 0.4, 1.2 mm.

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CHAPTER 4

4.1 HEAT TREATMENT

Hardening of steels is done for most applications that require the steel to be used as a tool to work other materials. Hardening may also be required for an application when high strength is required.

HEAT TREATMENT PROCESS FOR DAC10

Stress relieving done at 650°C for 2 hr 30 min.

Slow cooling to 500°C.

Dry Pre heating up to 650°C for 2 hr 30 min

Hardening done at 1010-1020°C for 45 min.

Mar Quenching-Salt bath at 550°C.

Air cooling to room temperature.

Checking the air quenched hardness.

1st Tempering at 550°C for 2hr 30 min.

2nd Tempering at 550°C for 2hr 30 min.

3rd Tempering at 550°C for 2hr 30 min.

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CHAPTER 5

5.1 CNC TURNING CENTRE SPECIFICATIONS

MODEL DX160 JYOTI CNC MACHINE

SR NO. 60000751-2010K

INPUT VOLTAGE 415±10%

INPUT POWER 15KW

SPINDLE POWER 5.5/7 KW

WORKING TEMPERATURE 10°C TO 50°C

SPINDLE SPEED RPM 50 TO 4000rpm

MAX RAPID SPEED 24000 mm/min

WEIGHT 3800 Kg (app)

CONTROLLER USED SIEMENS (SINUMERIC)

Table 3 CNC Turning Centre Specifications

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DX160 CNC TURNING CENTRE

Fig.6 CNC Turning Centre

EXPERIMENTAL SETUP

Fig.7 Experimental Setup

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Fig.8 Working on CNC lathe

Fig.9 Machining on Hot Work Tool Steel With Ceramic Tool Inserts

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CHAPTER 6

6.1 SURFACE INTEGRITY

Surface Integrity in the engineering sense can be defined as a set of various properties(both, superficial and in-depth) of an engineering surface that affect the performance of this surface in service. These properties primarily include surface finish, texture and profile; fatigue corrosion and wear resistance; adhesion and diffusion properties. Surface science can be defined as a branch of science dealing with any type and any level of surface and interface interactions between two or more entities. These interactions could be physical, chemical, electrical, mechanical, and thermal.

The term surface integrity is used to describe the quality and condition of the surface region of a component. The combination of stress and elevated temperatures generated during machining can lead to defects, or alterations of the microstructure, micro hardness, cause surface cracking, craters, folds, inclusions, plastic deformation and residual stresses in the finished part. Surface alterations may include mechanical, metallurgical, and chemical and other changes. These changes, although confined to a small surface layer, may limit the component quality or may, in some cases, render the surface unacceptable.

A basic understanding of the changes in the condition of the surface is very much required if improvement in product quality is to be attained. Surface integrity (SI) reveals the influence of surface properties and condition upon which materials are likely to perform. It has long been known that the method of surface finishing and the complex combination of surface roughness, residual stress, cold work, and even phase transformations strongly influence the service behavior of manufactured parts as Fatigue and stress corrosion.

The practical results of the surface texture will be affected by a number of different factors in the processes related to the cutting tool (stability, overhang, cutting geometry, tool wear), the machinery (stability, machining environment, coolant application, machine conditions, power and rigidity) and the work piece(material structure and quality, design, clamping, previous machining process). In particular, the resulting dynamic and static stability of the total process system is of vital consequence to the quality of surface texture achieved.

The surface integrity is produced in general (normal) and two extremes, i.e., gentle or abusive process. General refers to machining conditions that are normally achieved by utilizing the manufacturer’s recommendations and are expected in a conventional workshop. Gentle machining will occur when using the new tool with sharp cutting edges, which have a very small radius, typically below 10−20 μm. As a result, the surface integrity will be high due to marginal disturbance to the surface from the tertiary shear zone.

As the tool wear progresses, the radius of the cutting edge increases and a flat land appears from the clearance face. This causes that rubbing will increase between the tool and the work piece,

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and the abusive conditions result in low surface integrity. In addition, much heat is generated and a heat-affected layer produced has predominantly a negative influence on the surface functional performance. typical ranges of the roughness average (Ra) values achievablein many traditional machining operations under “normal” conditions, as well as Non-traditional processes. Higher or lower values of Ra may be obtained under various machining conditions.

THE DEFINED SI PARAMETERS ARE CLASSIFIED AS:

• Geometrical parameters (e.g., surface finish, texture, bearing curve parameters);

• Physical parameters (e.g., micro hardness, residual stresses, microstructure);

• Chemical parameters (e.g., affinity oxidation, adsorption, chemisorptions, surface electrical polarization, surface chemical reactions,);

• Biological parameters (e.g., cell attachment, cell proliferation).

VARIOUS DEFECTS ARE CAUSED BY AND PRODUCED DURING PART MANUFACTURING COMPROMISING SI

These defects can be classified as those of the original material and those imposed during manufacturing. Amongst many defects found in practice, the following are most common:

• Cracks are external or internal separations with sharp outlines. Cracks requiring a magnification of 10× or higher to be seen by a naked eye are called micro cracks.• Metallurgical transformation involves micro structural changes caused by temperature and high contact pressures. Included are phase transformations, re-crystallization, alloy depletion, decarburization, and molten and re-cast, re-solidified, or re-deposited material, as in electrical-discharge machining.• Residual stresses caused by process forces, deformations and temperatures.• Craters are shallow depressions.• Pits are shallow surface depressions, usually the result of chemical or physical attack.• Plastic deformation is a severe surface deformation caused by high stresses due to friction or tool in manufacturing.

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Fig.10 Significance of Surface Integrity

6.2 SURFACE ROUGHNESS

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Surface roughness refers to the high frequency irregularities on the surface caused by the interaction of the material microstructure and the cutting tool action. This relates directly to the manufacturing unit event (the inherent generating mechanisms) and describes the irregularities caused by each feed rate, abrasive grit, particle, or spark. Geometrically, the surface is seen to have a large number of minute irregularities (peaks and valleys) superimposed on more widely spaced undulations (waviness). Nose radius and feed rate have the greatest impact on surface finish.

The concept of roughness is often described with terms such as ‘uneven’, ‘irregular’, ‘coarse in texture’, ‘broken by prominences’. Similar to some surface properties such as hardness, the value of surface roughness depends on the scale of measurement. In addition, the concept roughness has statistical implications as it considers factors such as sample size and sampling interval. All these features determine to a great extent the behavior of the part in service. Thus, for example, surface finish has a significant effect on the frictional and lubricant-retention properties of the surface. Waviness determines whether mating will be accurate so that leakage can be avoided in sealed joints, metallurgical damage affects the wear resistance of the part and residual stresses influence the fatigue strength of critical parts besides causing harmful deformations. Therefore, it is evident that 'surface quality' is of critical importance and its proper evaluation is of utmost interest to the shop engineer.

Fig.11 Surface Roughness Meter circuit

CHAPTER 7

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7.1 DESIGN OF EXPERIMENT

These are the designs where only one factor is under investigation, and the objective is to determine whether the response is significantly different at different factor levels. The factor can be qualitative or quantitative. In the case of qualitative factors (e.g. different suppliers, different materials, etc.), no extrapolations (i.e. predictions) can be performed outside the tested levels, and only the effect of the factor on the response can be determined. On the other hand, data from tests where the factor is quantitative (such as temperature, voltage, load, etc.) can be used for both effect investigation and prediction, provided that sufficient data is available. In DOE++, predictions for one factor designs can be performed by transferring the data to the Multiple Linear Regression tool available in the Other Tools in the Project Tree.

FACTORIAL DESIGNSIn factorial designs, multiple factors are investigated simultaneously during the test. As in one factor designs, qualitative and/or quantitative factors can be considered. The objective of these designs is to identify the factors that have a significant effect on the response, as well as investigate the effect of interactions (depending on the experiment design used). Predictions can also be performed when quantitative factors are present, but care must be taken since certain designs are very limited by the choice of the predictive model. For example, in two level designs only a linear relationship can be used between the response and the factors, which may not be realistic. 

General Full Factorial DesignsIn general full factorial designs, each factor can have different number of levels, and the factors can be quantitative or qualitative or both. In this version of DOE++, the software always converts all the factors into a qualitative space, therefore no predictions can be performed for this design.

Two Level Full Factorial DesignsThese are factorial designs where the number of the levels for each of the factors is restricted to two. Restricting the levels to two and running a full factorial experiment reduces the number of treatments (compared to a general full factorial experiment), and allows for the investigation of all the factors and all their interactions. If all factors are quantitative, then the data from such experiments can be used for predictive purposes, provided a linear model is appropriate for modeling the response (since only two levels are used, curvature cannot be modeled).

Two Level Fractional Factorial DesignThis is a special category of two level designs, where not all factor level combinations are considered, and the experimenter can choose which combinations are to be excluded. Based on the excluded combinations, certain interactions cannot be determined.

Plackett-Burman Design

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This is a special category of two level fractional factorial designs, proposed by R. L. Plackett and J. P. Burman, where only a few specifically chosen runs are performed to investigate just the main effects (i.e. no interactions).

Taguchi's Orthogonal ArraysTaguchi's orthogonal arrays are highly fractional designs, used to estimate main effects using only a few experimental runs. These designs are not only applicable to two level factorial experiments, but also can investigate main effects when factors have more than two levels. Designs are also available to investigate main effects for certain mixed level experiments where the factors included do not have the same number of levels.

RESPONSE SURFACE METHOD DESIGNSThese are special designs that are used to determine the settings of the factors to achieve an optimum value of the response.

RELIABILITY DOEThis is a special category of DOE where traditional designs, such as the two level designs, are combined with reliability methods to investigate effects of different factors on the life of a unit. In Reliability DOE, the response is a life metric (e.g. age, miles, cycles, etc.), and the data may contain censored observations (suspensions, interval data). One factor, and two level factorial designs (full, fractional, and Plackett-Burman) are available in DOE++ to conduct a Reliability DOE analysis

7.2 TAGUCHI ORTHOGONAL ARRAYS

The Taguchi method involves reducing the variation in a process through robust design of experiments. The overall objective of the method is to produce high quality product at low cost to the manufacturer. The Taguchi method was developed by Dr. Genichi Taguchi of Japan who maintained that variation. Taguchi developed a method for designing experiments to investigate how different parameters affect the mean and variance of a process performance characteristic that defines how well the process is functioning. The experimental design proposed by Taguchi involves using orthogonal arrays to organize the parameters affecting the process and the levels at which they should be varied. Instead of having to test all possible combinations like the factorial design, the Taguchi method tests pairs of combinations. This allows for the collection of the necessary data to determine which factors most affect product quality with a minimum amount of experimentation, thus saving time and resources. The Taguchi method is best used when there are an intermediate number of variables (3 to 50), few interactions between variables, and when only a few variables contribute significantly.

The Taguchi arrays can be derived or looked up. Small arrays can be drawn out manually; large arrays can be derived from deterministic algorithms. Generally, arrays can be found online. The arrays are selected by the number of parameters (variables) and the number of levels (states). This is further explained later in this article. Analysis of variance on the collected data from the Taguchi design of experiments can be used to select new parameter values to optimize the performance characteristic. The data from the arrays can be analyzed by plotting the data and

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performing a visual analysis, ANOVA, bin yield and Fisher's exact test, or Chi-squared test to test significance.

THE GENERAL STEPS INVOLVED IN THE TAGUCHI METHOD ARE AS FOLLOW:

1. Define the process objective, or more specifically, a target value for a performance measure of the process. This may be a flow rate, temperature, etc. The target of a process may also be a minimum or maximum; for example, the goal may be to maximize the output flow rate. The deviation in the performance characteristic from the target value is used to define the loss function for the process.

2. Determine the design parameters affecting the process. Parameters are variables within the process that affect the performance measure such as temperatures, pressures, etc. that can be easily controlled. The number of levels that the parameters should be varied at must be specified. For example, a temperature might be varied to a low and high value of 40 C and 80 C. Increasing the number of levels to vary a parameter at increases the number of experiments to be conducted.

3. Create orthogonal arrays for the parameter design indicating the number of and conditions for each experiment. The selection of orthogonal arrays is based on the number of parameters and the levels of variation for each parameter, and will be expounded below.

4. Conduct the experiments indicated in the completed array to collect data on the effect on the performance measure.

5. Complete data analysis to determine the effect of the different parameters on the performance measure.

Fig.12 Array Selection

7.3 SELECTION OF ORTHOGONAL ARRAY

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DESIGN SCHEME OF CUTTING PARAMETERS AND THEIR LEVELS

Table 4 Parameters Selected

The degrees of freedom for 3 level and four parameters is 8.The orthogonal array selected for 3 level and four parameter model is L9.

Parameter Symbol Unit Level

1 2 3

Cutting Speed ʋ m/min 50 150 250

Feed f mm/rev 0.1 0.15 0.2

Depth Of Cut d mm 0.2 0.3 0.4

Nose Radius R mm 0.4 0.8 1.2

Table 5 L9 Orthogonal Array

CHAPTER 8

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8.1 METHODOLOGY ADOPTED

MATERIAL SELECTION

TOOL SELECTION

COMPOSITION TEST

HEAT TREATMENT

DESIGN OF EXPERIMENT

HARD TURNING

EVALUATION OF SURFACE ROUGHNESS AND TOOL WEAR

CONCLUSIONAND REFERENCES

Fig.13 Methodology Flow Chart

8.2 OBSERVATION DATA

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Table 6 Observation Data

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Response 1 RaTransform: Square Root Constant: 0 ANOVA for Response Surface Linear ModelAnalysis of variance table [Partial sum of squares - Type III]

Sum of Mean F p-valueSource Squares df Square Value Prob > FModel 1.592332202 4 0.398083 40.2591611 0.0017 significant A-velocity 0.030773878 1 0.030774 3.112241276 0.1525 B-feed 0.697683116 1 0.697683 70.55848506 0.0011 C-depthof cut 0.005149489 1 0.005149 0.520781055 0.5104 D-nose radius 0.858725719 1 0.858726 86.84513699 0.0007Residual 0.039552046 4 0.009888Cor Total 1.631884248 8

Table 7 ANOVA model

The Model F-value of 40.26 implies the model is significant. There is onlya 0.17% chance that a "Model F-Value" this large could occur due to noise.

Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case B, D are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy),

model reduction may improve your model.

Std. Dev. 0.099438 R-Squared 0.975762958Mean 1.029461 Adj R-Squared 0.951525917C.V. % 9.659273 Pred R-Squared 0.872730329PRESS 0.207689 Adeq Precision 20.37644133

The "Pred R-Squared" of 0.8727 is in reasonable agreement with the "Adj R-Squared" of 0.9515."Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. Your

ratio of 20.376 indicates an adequate signal. This model can be used to navigate the design space.

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STATISTICAL MODEL DEVELOPED:

Ra = 0.56778 + 0.000716 * A + 6.819 * B + 0.29 C - 0.945 *D.

Where:

Ra=Surface Roughness, A=Velocity, B=feed, C=Depth of cut, D=Nose Radius.

8.3 GRAPHS

Graph 1 Contour Plot of Ra Vs Velocity, Feed

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Graph 2 Contour Plot of Ra Vs. Velocity, Depth Of Cut

Graph 3 Contour Plot of Ra Vs. Velocity, Nose Radius

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Graph 4 Contour Plot of Ra Vs Feed, Nose Radius

Graph 5 Contour Plot of Ra Vs Feed, Depth of Cut

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Graph 6 Contour Plot of Ra Vs Depth of cut, Nose Radius

Graph 7 Predicted Vs Actual Graph

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CHAPTER 9

9.1 CONCLUSION:

The following conclusions can be drawn by the experimental study on hard turning of DAC10 (Hot Work Tool Steel) with AB2010 ceramic tool inserts.

The cutting speed, feed rate, depth of cut and nose radius are statistically significant factors in influencing the surface roughness of DAC10, it explains 1.90%, 42.9%, 0.31% and 52.7% respectively by turning of DAC10.

The least average surface roughness value of 0.17 µm is achieved at a velocity of 150 m/min, feed 0.1 mm/rev, depth of cut 0.3 and using a tool insert of 1.2 mm nose radius. This indicates the average surface roughness value is least when the velocity is medium, low feed, medium depth of cut and high nose radius.

The highest average surface roughness value of 3.56 is achieved at a velocity of 250 m/min, feed 0.2 mm/rev, depth of cut 0.3 mm and using a tool insert of 1.2 mm nose radius. At high velocity, feed, nose radius and medium depth of cut the average surface roughness is high.

The contour graphs of Ra Vs Velocity, Feed, Ra Vs Velocity, Depth of cut, Ra Vs Velocity, Nose radius are plotted which denote the variation of the average surface roughness value accordingly.

The relation between the factors and performance measures are expressed by the statistical equation which can be used to estimate the expected values of the performance levels for the any factor level.

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9.2 REFERENCE

Fundamentals of Metal Cutting and Machine Tools; B.L Juneja,G.S. Sekhon, Nitin Seth.

Tool Steels 5th Edition; George Roberts, George Krauss, Richard Kennedy.

Engineering Materials Properties and Selection; Kenneth G. Budinski, Michael K. Budinski.

Product Design and Manufacturing 3rd Edition By A.K Chitale, R.C. Gupta.,2005

TQM by Subburaj 2005 Ramasamy, TMH Delhi.2005

Optimising Engineering Designs By J. Krottmaier,1993.

Design and Analysis of Experiments By Angela Dean, Daniel Voss, 2006,New Delhi.

Design of Experiments By Jiju Autony, Elsevier, Great Britain, 2005

Introduction to the Design and Analysis of Experiments,Geoffrey M.Clarke And Robert E Kempson.(Arnold Publisher) 1997, New York.

Design of Experimentby R.J Delvecchio,Hanser Publisher,Carl Hansev Verleng,1997,Germany.

27th Machieneries Hand Book,Industrial Press 2004.

Machining Data Hand Book. TQM Engineering Hand Book By D.H.Stamatis,1997,Marcel Dekker,New York.

Hard Turning of Cold Work Tool Steel Using Wiper Ceramic Tool. Noordin Mohd. Yusof, Affandi M. Zainal, Hendriko, Denni Kurniawan Faculty Of Mechanical Engineering University Technology Malaysia 81310 Skudai, Johor Bahru.