Optimization of Friction Welding Parameters in Dissimilar Materials Using Taguchi’S Method Dr

International Journal of Advanced Science and Technology Vol. 29, No. 03, (2020), pp. 4629 - 4642 Optimization of Friction Welding Parameters in Dissimilar Materials using Taguchi’s Method Dr. R N. Ramanujam1, Dr. S. Krishnamohan2, 1,2Professor Dept of Mechanical Engineering E.G.S. Pillay Engineering College Nagapattinam Abstract At present there are various welding process is introduced among them there is Friction welding (FW) is a fairly recent technique that utilizes a non on sumable welding tool to generate frictional heat and plastic deformation at the welding location, There by affecting the formation of a joint while the material is in solid state. The technique can produce joints utilizing equipment based on traditional machine tool technologies, the main aim of this paper to obtained friction weld element of dissimilar material and optimizing the friction welding parameters in order tom establish the weld quality. Taguchi method is applied for optimizing the welding parameters to attain maximum tensile strength of the joint and hardness of the welded joint. It is widely used in aerospace and automotive industrial applications. The process parameters play a major role in determining the high tensile strength of the weld of dissimilar materials.1.Rotational speed, 2.Friction pressure, 3.Friction time, 4.Forge pressure.

1. I.NTRODUCTION: Welding is the process of joining two or more pieces of the same or dissimilar materials to achieve complete coalescence. It is the process of joining similar or dissimilar metals by the application of heat with or without the application of pressure and addition filler metal. The edges of the metal pieces to be welded are brought to plastic state by the heat or filler metal is added and on cooling, the pieces join together and a permanent joint is produced. There is various methods are available 1. GAS WELDING: classified as; Air acetylene welding, Oxy acetylene welding, Oxy hydrogen welding ,. Process gas welding

2. ARC WELDING: classified as;. Carbon ARC welding, flux cored ARC welding. Gas tungsten welding, plasma ARC welding, gas metal ARC welding , Shielding metal ARC welding 3. RESISTANCE WELDING: classified as Resistance spot welding, projection welding, Resistance seam welding , flash welding ,. upset welding , percussion welding ,High frequency resistance welding 5. OTHER WELDING PROCESS: classified as; Electro slag welding , Electron beam welding, Laser beam welding, Induction welding ,Thermit welding 6. SOLID STATE WELDING: classified as; Cold welding, diffusion welding, Explosion welding, forge welding,. friction welding , Hot pressure welding ,Roll welding, Ultra sonic welding

1.1 FRICTION WELDING A method of operating on a work piece comprises offering a probe of material harder than the work piece to the continuous surface of the work piece of the causing relative cyclic movement between the probe on the work piece will urging the probe and work piece together whereby frictional heat is generated as the probe enters the work piece so as to create a plasticized region

International Journal of Advanced Science and Technology Vol. 29, No. 03, (2020), pp. 4629 - 4642 in the work piece material around the probe, stopping the relative cyclic movement, and allowing the plasticized material to solidify around the probe. This technique, which we refer to as “friction welding” provides a very simple method of joining a probe to a work piece.

1.2. TYPES OF FRICTION WELDING:

Linear Friction Welding Spin Welding Rotary Friction Welding Inertia Friction Welding Friction Surfacing Friction Stud Welding Friction Stir Welding

Friction stir welding (FSW) is a novel welding technique invented by The Welding Institute (TWI) in 1991. FSW is actually a solid-state joining process that is a combination of extruding and forging and is not a true welding process. Since the process occurs at a temperature below the melting point of the work piece material, FSW has several advantages over fusion welding. Some of the process advantages are given in the following list:

1. FSW is energy efficient. 2. FSW requires minimal, if any, consumables. 3. FSW produces desirable microstructures in the weld and heat-affected zones 4. FSW is environmentally “friendly” (no fumes, noise, or sparks) 5. FSW can successfully join materials that are “unweldable” by fusion welding methods. 6. FSW produces less distortion than fusion welding techniques. Many dissimilar metal combination can be joined and there are a number of process variation including:

1.3.SPIN WELDING: Four different phases can be distinguished in the vibration welding process, the solid friction phase, the transient phase, the steady state phase, the cooling phase. 1. In the solid friction phase the heat is generated as a result of friction between two surfaces. This causes the polymer material to heat up until the melting point is reached. The heat generated is dependent on applied tangential velocity and pressure. 2. In the second phase a thin molten polymer is formed which grows as a result of ongoing heat generation. In this stage hest is produced by viscous dissipation. At first only a thin molten layer exists and consequently the shear rate and viscosity heating contribution are large. As the thickness of molten layer increases the degree of viscous heating decreases. 3. Thereafter (start of third phase) the melting rate equals the outward flow rate (steady state). As soon as the phase has been reached, the thickness of molten layer is constant. The steady state is maintained until a certain melt down depth has been reached, at which point the rotation is stopped.

International Journal of Advanced Science and Technology Vol. 29, No. 03, (2020), pp. 4629 - 4642 4. At this point (phase 4) the polymer melt cools and solidification starts, while film drainage still occurs since the welding pressure remains. After all the materials has solidified, drainage stops and join is formed.

1.4. APPLICATION OF FRICTION WELDING: It can be used for various applications: Commercial , Aerospace, Hydraulic, Automobiles, Bi-metal:

2. TAGUCHI METHOD The technique of laying out the conditions of experiments involving multiple factors was first proposed by the Englishman sir R.A. Fisher. The method is popularly known as the factorial design of experiment. A full factorial design will identify all possible combination for a given set of factors. Since most industrial experiment usually involve significant number of factors, a full factorial design results in a large number of experiment. To reduce the number of experiments to a practical level, only a small set from all the possibilities is selected. The method of selecting a limited number of experiments which produces the most information is known as a partial fraction experiments. Although this method is well, there are no general guidelines for its application or the analysis of the results obtained by performing the experiments. Taguchi constructed a special set of general design guidelines for factorial experiments that cover many application. Taguchi has envisaged a new method of conducting design of experiments which are based on well defined guidelines. This method uses a special set of array called orthogonal arrays. These standard arrays stipulate the way of conducting the minimal number of experiments which could give the full information of all the factors that affect the performance parameter. The crux of the orthogonal arrays method lies in choosing the level combinations of the input design variables for each experiment. 2.1. A TYPICAL ORTHOGONAL ARRAY There are many standard orthogonal arrays available, each of the arrays is meant for a specific number of independent design variables and levels. For example, if one wants to conduct an experiment to understand the influence of 3 different independent variables with each variable having 3 set values (level values), then an L9 orthogonal array might be the right choice. The L9 orthogonal array is meat for understanding the effect of 3 independent factors each having 3 factor level values. This array assumes that there is no interaction between any two factors. While in many cases, no interaction model assumption is valid, there the some cases where is a clear evidence of interaction. A typical case of interaction would be the interaction between the metrical properties and temperature

2.2. ORTHOGONAL AARRAY

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The table 2.1 shows an L9orthogonal array. There are totally 9 experiments to be conduct and each experiment is based on the combination of level values as show in the table. For example, the third experiment is conducted by keeping the independent design variable 1 at level1, variable 2 at level 3 and variable 3 at level

2.3 PROPERTIOES OF AN ORTHOGONAL ARRAY The orthogonal arrays have the following special properties that reduce number of experiments to be conducted.

 The vertical column under each independent variable of the above has a special combination of level settings. All the level settings appear an equal number of times. For L9 array under variable3, level 1, level 2 and level 3appears thrice. This is called the balancing property of orthogonal arrays.

 All the level values of independent variable are used for conducting the experiments. 3. The sequence of level values for conducting the experiments shall not be changed. The reason for this is that the arrays of each factor columns are mutually orthogonal to any other column of level values. The inner product of vectors corresponding to weight is zero. If the above 3 levels

International Journal of Advanced Science and Technology Vol. 29, No. 03, (2020), pp. 4629 - 4642 are normalized between -1 and, then the weighing factors for level 1,level 2 , level 3 are -1 , 0 ,1respectively

2.4 MINIMUM NUMBER OF EXPERIMENTS TO BE CONDUCTED The design of experiments using the orthogonal array is, in most cases, efficient when compared to many other statistical designs. The minimum number of experiments that are required to conduct the Taguchi method can be calculated based on the degrees of freedom approach. For example, in case of 8 independent variables study having 1 independent variable with 2 levels and remaining 7 independent variables with 3 levels (L9 orthogonal) , the minimum number of experiments required based on the above equation is 16. Because of the balancing property of the orthogonal arrays, the total number of experiments for the above case is 1

3 ASSUMPTIONS OF THE TAGUCHI’S METHOD The additive assumption implies that the individual or main effects of the independent variables on performance parameter are separable. Under this assumption, the effect of each factor can be linear, quadratic or of higher order, but the model assumes that there exists no cross product effects (interactions) among the individual factors. That means the effect of independent variable 1 on performance parameter does not depend on the different level settings of any other independent variables and vice versa. If at any time, this assumption is violated, then the additively of the main effects does not hold, and the variables interact.

3.1 DESIGNING AN EXPERIMENT The design of an experiment involves the following steps 1. Selection of independent variables 2. Selection of number of level settings for each independent variable 3. Selection of orthogonal array 4. Assigning the independent variables to each column 5. Conducting the experiments 6. Analyzing the data 7. Inference The details of the above steps are given below.

3.2.SELECTION OF THE INDEPENDENT VARIABLES Before conducting the experiment, the knowledge of the product/process under investigation is of prime importance for identifying the factor likely to influence the outcome. In order to compile a comprehensive list of factors, the input to the experiment is generally obtained from all the people involved in this work

3.3.DECIDING THE NUMBER OF LEVELS Once the independent variables are decided, the number of levels for each variable is decided. The selection of number of levels depends on how the performance parameter is affected due to different level settings. If the performance parameter is a linear function of the independent

International Journal of Advanced Science and Technology Vol. 29, No. 03, (2020), pp. 4629 - 4642 variable, then the number of level setting shall be 2. However, if the independent variable is not linearly related, then one could go for 2, 3 or higher levels depending on whether the relationship is quadratic, cubic or order. In the absence of exact nature of relationship between the independent variable and the performance parameter, one could choose 2 level settings. After analyzing the experimental data, one can decide whether the assumption of level setting is right or not based on the percent contribution and the error calculations.

3.4. SELECTION OF AN ORTHOGONAL ARRAY Before selecting the orthogonal array, the minimum number of experiments to be conducted shall be fixed based on the total number of degrees of freedom present in the study. The minimum number of experiments that must be run to study the factors shall be more than the total degrees of freedom available. In counting the total degrees of freedom the investigator commits 1degree of freedom to the overall mean of the response under study. The number of degrees of freedom associated with each factor under study equals one less than the number of levels available for that factor. Hence the total degree of freedom without interaction effect is 1 + as Already given by equation 2.1. for example, in case of 9 independent variables, each having 2 levels, the total degrees of freedom is 9. Hence the selected orthogonal array shall have at least 9 experiments. An L9 orthogonal satisfies this requirement. Once the minimum number of experiment is decided, the further selection of orthogonal array is based on the number of independent variables and number of factor levels for each independent variable.

3.5. ASSIGING THE INDEPENDENT VARIABLES TO COLUMNS The order in which the independent variables are assigned to the vertical column is very essential. In case of mixed level variables and interaction between variables. The variables are to be assigned at right columns as stipulated as the orthogonal array. Finally, before conducting the experiment, the actual level values of each design variables shall be decided. It shall be noted that the significance and the percent contribution of the independent variables changes expending on the level values assigned. It the designer’s responsibility to set proper level values.

3.6. CONDUCTING THE EXPERIMENT Once the Orthogonal array is selected, the experiments are conducted as per the level combinations. It is necessary that all the experiments be conducted. The interaction columns and dummy variable columns shall not be considered for the conducting experiments, but are needed while analyzing the data to understand the interaction effect. The performance parameter under study is noted down for each experiment to conduct the sensitivity analysis.

3.7. INFERENCE From the above experimental analysis, it is clear that the higher the value of sum of square of an independent variable, the more it has influence on the performance parameter. One can also calculate the ratio of individual sum of square of a particular independent variable to the total sum of squares of all the variables. This ratio given the percent contribution of the independent

International Journal of Advanced Science and Technology Vol. 29, No. 03, (2020), pp. 4629 - 4642 variable on the performance parameter. In addition to above, one could find the near optimal solution to the problem. This near optimum value may not be global optimal solution. However, the solution can be used as an initial/ starting value for the standard optimization technique.

3.8 ROBUST DESIGN A main cause of poor yield in manufacturing processes is the manufacturing variation. These manufacturing variations include variation in temperature or humidity, variation in raw materials, and drift of process parameters. These sources of noise/ variation are the variables that are impossible or expensive to control The objective of the robust design is to find the controllable process parameter settings for which noise or variation has a minimal effect on the product’s or process’s functional characteristics. It is to be noted that the aim is not to find the parameter settings for the uncontrollable noise variables, but the controllable design variables. To attain this objective, the control parameters, also known as inner array variables, are systematically varied as stipulated by the inner Orthogonal array. For each experiment of the inner array, a series of new experiments are conducted by varying the level settings of the uncontrollable noise variables. The level combinations of noise variables are done using the outer orthogonal array. The influence of noise on the performance characteristics can be found using the ratio where S is the standard deviation of the performance parameters for each inner array experiment and N is the functional variation due to noise. Using this result, it is possible to predict which control parameter settings will make the process insensitive to noise.

4. EXPERIMENTAL PROCEDURE 4.1 MACHINING: In this experiment of friction welding, one end of the plate is fixed with the help of chuck and one end of the plate is welded to dead centre of tail stock. Then the plate attached to then chuck is rotated and the other plate is pushed towards it by applying pressure manually. In the chapter, the various experimental process of friction welding are described in detail. In literature survey they are choosing the parameters are Rotating speed, Friction time, Friction pressure, Forging pressure they are changing these parameter for their investigation. We are choosing the parameters are Heating pressure, Heating time, and upsetting time in our project. Various operations that have conducted during the experiment are described below: Raw materials size (As received)

Aluminium 6061 Mild steel Diameter-16mm Diameter-16mm Length-100mm Length-100mm

Raw material size (after machining)

Aluminium 6061 Mild steel Diameter-16mm Diameter-16mm Length-90mm Length-80mm

Total number of pieces

Aluminium 6061-10 Mild steel-10

Total number of joints

International Journal of Advanced Science and Technology Vol. 29, No. 03, (2020), pp. 4629 - 4642 Aluminium 6061-9 Mild steel-9

4.2. PARAMETERS OF THE FRICTION WELDING:

Heating pressure Variables: Levels: Upsetting time V1-Heating pressure 1-Low Heating time V2-Upsetting time 2-Medium Upsetting V3-Heating time 3-High pressure Rotating Speed  4.3. PARAMETERS FOR 9 TRIALS: Rotating speed : 1300rpm (constant at all trails) Upsetting Pressure: 40bar (constant at all trails)

TRAIL TRAIL TRAIL TRAIL TRAIL TRAIL TRAIL TRAIL TRAIL NO: 1 NO: 2 NO: 3 NO:42 NO: 5 NO: 6 NO: 7 NO: 8 NO: 9

Heating Heating Heating Heating Heating Heating Heating Heating Heating pressure: pressure: pressure: pressure: pressure: pressure: pressure: pressure: pressure: 20 bar 20 bar 20 bar 25 bar 25 bar 25 bar 30 bar 30 bar 30 bar Upsetting Upsetting Upsetting Upsetting Upsetting Upsetting Upsetting Upsetting Upsetting time : 4 time : 7 time : 10 time : 7 time : 10 time : 4 time : 10 time : 4 time : 7 sec sec sec sec sec sec sec sec sec Heating Heating Heating Heating Heating Heating Heating Heating Heating time : 4 time : 7 time : 10 time : 4 time : 7 time : 10 time : 4 time : 7 time : 10 sec sec sec sec sec sec sec sec sec

4.4. TENSILE TESTING: Tensile testing, also known as tension testing, is a fundamental materials science test in which a sample is subjected to a controlled tension until failure. The results from the test are commonly used to select a material for an application, for quality control, and to predict how a material will react under other types of forces. Properties that are directly measured via a tensile test are ultimate tensile strength, maximum elongation and reduction in area. From these measurements the following properties can also be determined: Young’s modulus, passion’s ratio ,yield strength, and strain-hardening characteristics. A tensile specimen is a standardized sample cross- section. It has two shoulders and a gauge (section) in between. The shoulders are large so they can be readily gripped, whereas the gauge section has a smaller cross-section so that the deformation and failure can occur in this area.

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The most common testing machine used in tensile testing is the universal testing machine. This type of machine has two crossheads; one is adjusted for the length of the specimen and the other is driven to apply tension to the test specimen. There are two types: hydraulic powered and electromagnetically powered machines. The machine must have the proper capabilities for the test specimen being tested. There are four main parameters: force capacity, speed, and precision and accuracy. Force capacity refers to the fact that the machine must be able to generate enough force to fracture the specimen. The machine must be able to apply the force quickly or slowly enough to properly mimic the actual application. Finally, the machine must be able to accurately and precisely measure the gauge length and forces applied; for instance, a large machine that is designed to measure long elongations may not work with a brittle material that experiences short elongation prior to fracturing. Alignment n of the test specimen in the testing machine is critical, because if the specimen is misaligned, either at an angle or offset to one side, the machine will exert a bending force on the specimen. This is especially bad for brittle materials, because it will dramatically skew the results. This situation can be minimized by using spherical seats or U- joints between the grips and the test machine. If the initial portion of the stress-strain curve is curved and not linear, its indicates the specimen is misaligned in the testing machine. The strain measurements are most commonly measured with an extensometer, but strain gauges are also frequently used on small test specimen or when Poisson’s ratio is being measured.

4.5. P1–TENSILE TESTING SPECIMEN BEFORE WELDING

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F1 – FRICTION WELDING MACHINE: P2-TENSILE TESTING SPECIMEN AFTER WELDING:

F2 – TENSILE TESTING MACHINE:

5. CALCULATION AND TABULATION 5.1.T1-1.9 ORTHOGONAL ARRAY

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5.2. T2 VARIABLES RANGE:

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6. RESULT AND DISCUSSION 6.1 TENSILE TESTING: The ultimate tensile strength of 9 trails of different parameters as per the Taguchi’s technique is given in the table T5 The maximum tensile strength obtained in the 5th trail for the parameters of heating pressure 25 bar, upsetting time 10sec, heating time 7sec. The maximum tensile strength 172 Mpa .The minimum tensile strength obtained in the 4th trail for the parameters of heating pressure 25bar, upsetting time 4sec, heating time 4sec.The minimum tensile strength 144Mpa.

6.2. CONCLUSION: A statistical approach namely is design experiments a Taguchi’s technique was utilized to plan and minimize the number of experiment, at the same time making reliable inference from the results. The influence of processing parameters foe the tensile property and fracture location where analyzed The optimum parameters where obtained for maximum weld strength .The welding strength is lower than base metal strength.

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